{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "#导入必要的工具包\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from sklearn.cluster import MiniBatchKMeans\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn import metrics\n",
    "\n",
    "from sklearn.decomposition import PCA\n",
    "import time\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
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       "      <td>2012-10-27T00:00:00.001Z</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>2012-10-31T10:00:00.003Z</td>\n",
       "      <td>Malang</td>\n",
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       "      <td>Indonesia</td>\n",
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       "   Unnamed: 0    event_id     user_id                start_time     city  \\\n",
       "0           0  1845469953  2522958388  2012-08-18T03:00:00.003Z      NaN   \n",
       "1           1   715927047  2897297904  2012-09-30T01:00:00.003Z  Oakland   \n",
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       "4           4   741936389  3930427944  2012-10-31T10:00:00.003Z   Malang   \n",
       "\n",
       "  state  zip        country     lat      lng   ...     c_92  c_93  c_94  c_95  \\\n",
       "0   NaN  NaN            NaN     NaN      NaN   ...        0     0     0     1   \n",
       "1    CA  NaN  United States  37.752 -122.201   ...        0     0     2     0   \n",
       "2   NaN  NaN            NaN     NaN      NaN   ...        0     0     0     0   \n",
       "3   NaN  NaN            NaN     NaN      NaN   ...        0     0     0     0   \n",
       "4   NaN  NaN      Indonesia  -7.983  112.631   ...        0     0     0     0   \n",
       "\n",
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       "\n",
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     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#读入文件\n",
    "con_events=pd.read_csv(\"con_events.csv\")\n",
    "con_events.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
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       "   c_1  c_2  c_3  c_4  c_5  c_6  c_7  c_8  c_9  c_10   ...     c_92  c_93  \\\n",
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     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#筛选相应的特征进行聚类\n",
    "columns=con_events.columns\n",
    "columns=columns[10:]\n",
    "train=con_events[columns]\n",
    "train.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(13418, 101)"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train.shape "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "训练数据较多且维数较大，可先对其降维"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "#定义pca函数\n",
    "def pca(n_com, train):\n",
    "    \n",
    "    pca=PCA(n_components=n_com)#初始化PCA\n",
    "    pca.fit(train)#训练\n",
    "    train_pca=pca.transform(train)\n",
    "    return train_pca"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "#定义聚类函数\n",
    "def K_cluster_analysis(K, X_train, X_val):\n",
    "    \n",
    "    start = time.time()    \n",
    "    print(\"K-means begin with clusters: {}\".format(K));\n",
    "    \n",
    "    #K-means,在训练集上训练\n",
    "    mb_kmeans = MiniBatchKMeans(n_clusters = K) #聚类算法初始化\n",
    "    mb_kmeans.fit(X_train) #对训练集进行训练  \n",
    "    \n",
    "    # 在测试集上测试计算得分\n",
    "    CH_score = metrics.calinski_harabaz_score(X_val,mb_kmeans.predict(X_val))     \n",
    "    end = time.time()\n",
    "    \n",
    "    print(\"CH_score: {}, time elaps:{}\".format(CH_score, int(end-start)))\n",
    "    \n",
    "    return CH_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "h:\\python36\\lib\\site-packages\\sklearn\\model_selection\\_split.py:2026: FutureWarning: From version 0.21, test_size will always complement train_size unless both are specified.\n",
      "  FutureWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "主成分维数保留： 0.7\n",
      "K-means begin with clusters: 10\n",
      "CH_score: 5807.425525798887, time elaps:0\n",
      "K-means begin with clusters: 20\n",
      "CH_score: 6421.682230383581, time elaps:0\n",
      "K-means begin with clusters: 30\n",
      "CH_score: 5876.748082845563, time elaps:0\n",
      "K-means begin with clusters: 40\n",
      "CH_score: 5280.63542746045, time elaps:0\n",
      "K-means begin with clusters: 50\n",
      "CH_score: 3416.388539173391, time elaps:0\n",
      "K-means begin with clusters: 60\n",
      "CH_score: 4724.972838612355, time elaps:0\n",
      "K-means begin with clusters: 70\n",
      "CH_score: 4190.434655647569, time elaps:0\n",
      "K-means begin with clusters: 80\n",
      "CH_score: 5451.15417203281, time elaps:0\n",
      "K-means begin with clusters: 90\n",
      "CH_score: 12654.755855210902, time elaps:0\n",
      "K-means begin with clusters: 100\n",
      "CH_score: 12090.229678234533, time elaps:0\n",
      "主成分维数保留： 0.7107142857142856\n",
      "K-means begin with clusters: 10\n",
      "CH_score: 8970.667779820442, time elaps:0\n",
      "K-means begin with clusters: 20\n",
      "CH_score: 4705.433451528684, time elaps:0\n",
      "K-means begin with clusters: 30\n",
      "CH_score: 14047.788371364348, time elaps:0\n",
      "K-means begin with clusters: 40\n",
      "CH_score: 2579.6591421678318, time elaps:0\n",
      "K-means begin with clusters: 50\n",
      "CH_score: 3538.933174225985, time elaps:0\n",
      "K-means begin with clusters: 60\n",
      "CH_score: 7032.964094913977, time elaps:0\n",
      "K-means begin with clusters: 70\n",
      "CH_score: 1505.7131887015755, time elaps:0\n",
      "K-means begin with clusters: 80\n",
      "CH_score: 4057.387712073846, time elaps:0\n",
      "K-means begin with clusters: 90\n",
      "CH_score: 3013.712581288464, time elaps:0\n",
      "K-means begin with clusters: 100\n",
      "CH_score: 2011.565955527502, time elaps:0\n",
      "主成分维数保留： 0.7214285714285714\n",
      "K-means begin with clusters: 10\n",
      "CH_score: 5436.651631072805, time elaps:0\n",
      "K-means begin with clusters: 20\n",
      "CH_score: 10288.439430479897, time elaps:0\n",
      "K-means begin with clusters: 30\n",
      "CH_score: 10100.18520181447, time elaps:0\n",
      "K-means begin with clusters: 40\n",
      "CH_score: 8226.427923278414, time elaps:0\n",
      "K-means begin with clusters: 50\n",
      "CH_score: 9593.183010272734, time elaps:0\n",
      "K-means begin with clusters: 60\n",
      "CH_score: 4431.404140829005, time elaps:0\n",
      "K-means begin with clusters: 70\n",
      "CH_score: 4407.024386103478, time elaps:0\n",
      "K-means begin with clusters: 80\n",
      "CH_score: 3592.2296041020772, time elaps:0\n",
      "K-means begin with clusters: 90\n",
      "CH_score: 1942.697977766416, time elaps:0\n",
      "K-means begin with clusters: 100\n",
      "CH_score: 3436.4225938275777, time elaps:0\n",
      "主成分维数保留： 0.7321428571428571\n",
      "K-means begin with clusters: 10\n",
      "CH_score: 5022.828687003297, time elaps:0\n",
      "K-means begin with clusters: 20\n",
      "CH_score: 11134.100559117389, time elaps:0\n",
      "K-means begin with clusters: 30\n",
      "CH_score: 8902.74689564865, time elaps:0\n",
      "K-means begin with clusters: 40\n",
      "CH_score: 4432.623784089947, time elaps:0\n",
      "K-means begin with clusters: 50\n",
      "CH_score: 3026.1257543159045, time elaps:0\n",
      "K-means begin with clusters: 60\n",
      "CH_score: 5326.446745880029, time elaps:0\n",
      "K-means begin with clusters: 70\n",
      "CH_score: 2928.0366909766763, time elaps:0\n",
      "K-means begin with clusters: 80\n",
      "CH_score: 6689.767324549679, time elaps:0\n",
      "K-means begin with clusters: 90\n",
      "CH_score: 6769.064025080643, time elaps:0\n",
      "K-means begin with clusters: 100\n",
      "CH_score: 4128.160456053184, time elaps:0\n",
      "主成分维数保留： 0.7428571428571428\n",
      "K-means begin with clusters: 10\n",
      "CH_score: 7415.892653305651, time elaps:0\n",
      "K-means begin with clusters: 20\n",
      "CH_score: 2877.242921032448, time elaps:0\n",
      "K-means begin with clusters: 30\n",
      "CH_score: 8483.277968695254, time elaps:0\n",
      "K-means begin with clusters: 40\n",
      "CH_score: 4408.458309954361, time elaps:0\n",
      "K-means begin with clusters: 50\n",
      "CH_score: 4557.759823635595, time elaps:0\n",
      "K-means begin with clusters: 60\n",
      "CH_score: 3319.7064538344875, time elaps:0\n",
      "K-means begin with clusters: 70\n",
      "CH_score: 2848.8870613021954, time elaps:0\n",
      "K-means begin with clusters: 80\n",
      "CH_score: 9741.739484472024, time elaps:0\n",
      "K-means begin with clusters: 90\n",
      "CH_score: 1579.6766948512213, time elaps:0\n",
      "K-means begin with clusters: 100\n",
      "CH_score: 2031.7165779148204, time elaps:0\n",
      "主成分维数保留： 0.7535714285714286\n",
      "K-means begin with clusters: 10\n",
      "CH_score: 8312.415659178105, time elaps:0\n",
      "K-means begin with clusters: 20\n",
      "CH_score: 9600.088700179906, time elaps:0\n",
      "K-means begin with clusters: 30\n",
      "CH_score: 11204.50996478729, time elaps:0\n",
      "K-means begin with clusters: 40\n",
      "CH_score: 16653.319327410125, time elaps:0\n",
      "K-means begin with clusters: 50\n",
      "CH_score: 4462.163867090354, time elaps:0\n",
      "K-means begin with clusters: 60\n",
      "CH_score: 3923.212478713782, time elaps:0\n",
      "K-means begin with clusters: 70\n",
      "CH_score: 2419.969400988884, time elaps:0\n",
      "K-means begin with clusters: 80\n",
      "CH_score: 4440.944489282414, time elaps:0\n",
      "K-means begin with clusters: 90\n",
      "CH_score: 3007.9282470103326, time elaps:0\n",
      "K-means begin with clusters: 100\n",
      "CH_score: 2186.7562042077057, time elaps:0\n",
      "主成分维数保留： 0.7642857142857142\n",
      "K-means begin with clusters: 10\n",
      "CH_score: 9771.136171277973, time elaps:0\n",
      "K-means begin with clusters: 20\n",
      "CH_score: 4691.624268619005, time elaps:0\n",
      "K-means begin with clusters: 30\n",
      "CH_score: 7087.032911512194, time elaps:0\n",
      "K-means begin with clusters: 40\n",
      "CH_score: 3741.150758627719, time elaps:0\n",
      "K-means begin with clusters: 50\n",
      "CH_score: 11666.465713728136, time elaps:0\n",
      "K-means begin with clusters: 60\n",
      "CH_score: 8233.085616646476, time elaps:0\n",
      "K-means begin with clusters: 70\n",
      "CH_score: 5048.9448499661175, time elaps:0\n",
      "K-means begin with clusters: 80\n",
      "CH_score: 4948.678512642062, time elaps:0\n",
      "K-means begin with clusters: 90\n",
      "CH_score: 2886.900297980695, time elaps:0\n",
      "K-means begin with clusters: 100\n",
      "CH_score: 4852.793361439341, time elaps:0\n",
      "主成分维数保留： 0.7749999999999999\n",
      "K-means begin with clusters: 10\n",
      "CH_score: 5700.115570671412, time elaps:0\n",
      "K-means begin with clusters: 20\n",
      "CH_score: 7441.9391064726515, time elaps:0\n",
      "K-means begin with clusters: 30\n",
      "CH_score: 16417.31229734623, time elaps:0\n",
      "K-means begin with clusters: 40\n",
      "CH_score: 2269.759567525705, time elaps:0\n",
      "K-means begin with clusters: 50\n",
      "CH_score: 7128.820195087521, time elaps:0\n",
      "K-means begin with clusters: 60\n",
      "CH_score: 9297.41682983896, time elaps:0\n",
      "K-means begin with clusters: 70\n",
      "CH_score: 3723.161113187685, time elaps:0\n",
      "K-means begin with clusters: 80\n",
      "CH_score: 4870.566964224329, time elaps:0\n",
      "K-means begin with clusters: 90\n",
      "CH_score: 4293.152072057667, time elaps:0\n",
      "K-means begin with clusters: 100\n",
      "CH_score: 4590.07224251332, time elaps:0\n",
      "主成分维数保留： 0.7857142857142857\n",
      "K-means begin with clusters: 10\n",
      "CH_score: 10142.957225252845, time elaps:0\n",
      "K-means begin with clusters: 20\n",
      "CH_score: 7733.577766421305, time elaps:0\n",
      "K-means begin with clusters: 30\n",
      "CH_score: 11022.300841733024, time elaps:0\n",
      "K-means begin with clusters: 40\n",
      "CH_score: 2601.8914805619524, time elaps:0\n",
      "K-means begin with clusters: 50\n",
      "CH_score: 3658.0374282896196, time elaps:0\n",
      "K-means begin with clusters: 60\n",
      "CH_score: 18347.439508431475, time elaps:0\n",
      "K-means begin with clusters: 70\n",
      "CH_score: 6763.462037796504, time elaps:0\n",
      "K-means begin with clusters: 80\n",
      "CH_score: 5900.559812422268, time elaps:0\n",
      "K-means begin with clusters: 90\n",
      "CH_score: 6219.624039813495, time elaps:0\n",
      "K-means begin with clusters: 100\n",
      "CH_score: 2202.9807168234743, time elaps:0\n",
      "主成分维数保留： 0.7964285714285714\n",
      "K-means begin with clusters: 10\n",
      "CH_score: 4684.465129636257, time elaps:0\n",
      "K-means begin with clusters: 20\n",
      "CH_score: 8148.474687592444, time elaps:0\n",
      "K-means begin with clusters: 30\n",
      "CH_score: 7278.278543269318, time elaps:0\n",
      "K-means begin with clusters: 40\n",
      "CH_score: 9698.518034425811, time elaps:0\n",
      "K-means begin with clusters: 50\n",
      "CH_score: 4718.095921296797, time elaps:0\n",
      "K-means begin with clusters: 60\n",
      "CH_score: 10627.517696721652, time elaps:0\n",
      "K-means begin with clusters: 70\n",
      "CH_score: 7489.973705123775, time elaps:0\n",
      "K-means begin with clusters: 80\n",
      "CH_score: 7404.126787748893, time elaps:0\n",
      "K-means begin with clusters: 90\n",
      "CH_score: 2012.4831698317673, time elaps:0\n",
      "K-means begin with clusters: 100\n",
      "CH_score: 15549.063683828374, time elaps:0\n",
      "主成分维数保留： 0.8071428571428572\n",
      "K-means begin with clusters: 10\n",
      "CH_score: 10404.011448356938, time elaps:0\n",
      "K-means begin with clusters: 20\n",
      "CH_score: 4502.335165019778, time elaps:0\n",
      "K-means begin with clusters: 30\n",
      "CH_score: 20514.65389603977, time elaps:0\n",
      "K-means begin with clusters: 40\n",
      "CH_score: 4958.0594015484985, time elaps:0\n",
      "K-means begin with clusters: 50\n",
      "CH_score: 8400.579564286785, time elaps:0\n",
      "K-means begin with clusters: 60\n",
      "CH_score: 6853.098747862886, time elaps:0\n",
      "K-means begin with clusters: 70\n",
      "CH_score: 4344.191881926101, time elaps:0\n",
      "K-means begin with clusters: 80\n",
      "CH_score: 6058.184189171797, time elaps:0\n",
      "K-means begin with clusters: 90\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CH_score: 3417.561008700347, time elaps:0\n",
      "K-means begin with clusters: 100\n",
      "CH_score: 2709.7983228500734, time elaps:0\n",
      "主成分维数保留： 0.8178571428571428\n",
      "K-means begin with clusters: 10\n",
      "CH_score: 8572.03334386772, time elaps:0\n",
      "K-means begin with clusters: 20\n",
      "CH_score: 6605.766604793603, time elaps:0\n",
      "K-means begin with clusters: 30\n",
      "CH_score: 7663.936082245996, time elaps:0\n",
      "K-means begin with clusters: 40\n",
      "CH_score: 3593.107584819775, time elaps:0\n",
      "K-means begin with clusters: 50\n",
      "CH_score: 7984.443396338502, time elaps:0\n",
      "K-means begin with clusters: 60\n",
      "CH_score: 5239.887198076716, time elaps:0\n",
      "K-means begin with clusters: 70\n",
      "CH_score: 5871.704306215511, time elaps:0\n",
      "K-means begin with clusters: 80\n",
      "CH_score: 3189.8954639582143, time elaps:0\n",
      "K-means begin with clusters: 90\n",
      "CH_score: 4477.7662906509795, time elaps:0\n",
      "K-means begin with clusters: 100\n",
      "CH_score: 4016.979966868506, time elaps:0\n",
      "主成分维数保留： 0.8285714285714285\n",
      "K-means begin with clusters: 10\n",
      "CH_score: 6103.788402847937, time elaps:0\n",
      "K-means begin with clusters: 20\n",
      "CH_score: 7607.596907836535, time elaps:0\n",
      "K-means begin with clusters: 30\n",
      "CH_score: 6827.05999610319, time elaps:0\n",
      "K-means begin with clusters: 40\n",
      "CH_score: 2652.4587020506797, time elaps:0\n",
      "K-means begin with clusters: 50\n",
      "CH_score: 6106.221031731864, time elaps:0\n",
      "K-means begin with clusters: 60\n",
      "CH_score: 9476.385571459365, time elaps:0\n",
      "K-means begin with clusters: 70\n",
      "CH_score: 3541.4436428731583, time elaps:0\n",
      "K-means begin with clusters: 80\n",
      "CH_score: 2956.7742037130597, time elaps:0\n",
      "K-means begin with clusters: 90\n",
      "CH_score: 2194.8912491374394, time elaps:0\n",
      "K-means begin with clusters: 100\n",
      "CH_score: 2346.3177594750227, time elaps:0\n",
      "主成分维数保留： 0.8392857142857143\n",
      "K-means begin with clusters: 10\n",
      "CH_score: 9496.560931940756, time elaps:0\n",
      "K-means begin with clusters: 20\n",
      "CH_score: 5844.251384481908, time elaps:0\n",
      "K-means begin with clusters: 30\n",
      "CH_score: 8093.523224209852, time elaps:0\n",
      "K-means begin with clusters: 40\n",
      "CH_score: 6034.118344134792, time elaps:0\n",
      "K-means begin with clusters: 50\n",
      "CH_score: 6431.770824141746, time elaps:0\n",
      "K-means begin with clusters: 60\n",
      "CH_score: 6999.782414622117, time elaps:0\n",
      "K-means begin with clusters: 70\n",
      "CH_score: 19067.85188590137, time elaps:0\n",
      "K-means begin with clusters: 80\n",
      "CH_score: 3011.4624191435314, time elaps:0\n",
      "K-means begin with clusters: 90\n",
      "CH_score: 4297.8239623765885, time elaps:0\n",
      "K-means begin with clusters: 100\n",
      "CH_score: 5499.58660058227, time elaps:0\n",
      "主成分维数保留： 0.85\n",
      "K-means begin with clusters: 10\n",
      "CH_score: 9457.398299365504, time elaps:0\n",
      "K-means begin with clusters: 20\n",
      "CH_score: 5861.382103308019, time elaps:0\n",
      "K-means begin with clusters: 30\n",
      "CH_score: 5845.9869092081135, time elaps:0\n",
      "K-means begin with clusters: 40\n",
      "CH_score: 10507.991295285421, time elaps:0\n",
      "K-means begin with clusters: 50\n",
      "CH_score: 3779.27430749916, time elaps:0\n",
      "K-means begin with clusters: 60\n",
      "CH_score: 2796.7964195840905, time elaps:0\n",
      "K-means begin with clusters: 70\n",
      "CH_score: 11650.73189293713, time elaps:0\n",
      "K-means begin with clusters: 80\n",
      "CH_score: 3389.6622690518875, time elaps:0\n",
      "K-means begin with clusters: 90\n",
      "CH_score: 5992.441735345877, time elaps:0\n",
      "K-means begin with clusters: 100\n",
      "CH_score: 2451.410274372151, time elaps:0\n"
     ]
    }
   ],
   "source": [
    "#设置超参数搜索范围并计算得分\n",
    "n_coms=np.linspace(0.70, 0.85, num=15)\n",
    "Ks = [10, 20, 30,40,50,60,70,80,90,100]\n",
    "CH_scores=[]\n",
    "for n_com in n_coms:\n",
    "    #CH_scores=[]\n",
    "    train_pca=pca(n_com,train)\n",
    "    X_train, X_val = train_test_split(train_pca,train_size = 0.8,random_state = 0)\n",
    "    print(\"主成分维数保留：\",n_com)\n",
    "    for k in Ks:\n",
    "        ch=K_cluster_analysis(k, X_train,X_val)\n",
    "        CH_scores.append(ch)\n",
    "    #plt.plot(Ks, np.array(CH_scores))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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//fTTPvuaMWOG9e9q06ZNcs2aNVJKKd977z25bt26Xr++S5cuSX9/f9nQ0HBNxWWLre8nIEv2Y3yjZsyUEc1skeSUGfq1jNkhIcSfnDIDJrNlCCNTlOtbfXo6o2bNwnfJEswGA62lpY4OyellZGQQFhZGaGgo7u7upKSk8MUXX/TYPjU1lVWrVgEwc+ZMZsyYAcCkSZMYN24clZWVAMTGxhISEmKzj3feeYd77rmnS7mi3voSQlBbWwtATU1Nj7U8bfnss89YsmQJXl5e11Rc9qaKmCsj2snzdTQYzQMcmAXwwXel/P18HTdMHjOE0SnK9clcXU1jTg5jH34Iz1gdAI25ubj38MvO2bya8Sp/v/x3u/Y5K2AWz934XK9tKioqmDJlivW1Vqvl8OHDNtuWlpZSXFzM/PndK5lkZGRgNBqZPn16n/f7/PPP2bt3L5mZmTbbXNnX1q1bWbp0KZ6envj6+nLo0CFr2z/96U8cOHCAmTNn8tZbb3X5WqCtKPnPf/7zXmMa6XHZg5oxU0a0IwPY+N8hob2tqpupKEOj/uBfwWzGJymJUWFhuHh706QeAOiTtFEi8cpakR3S0tJITk5Go9F0OX7u3DkeeOAB3nvvPVxcev8V/9RTT/Hqq69266O3vt566y127NiBXq9n7dq11gHNXXfdRUlJCXl5edxxxx2sWbOmW1/Hjh1j8eLFvcY0kuOyFzVjpoxoR0oNBHqPQuvv2e9rJvl5MtnPk8xSAw/ePG0Io1OU61N9ejqasWPxmD0b4eKCZ0zMiHoAoK+ZraGi1WopLy+3vtbr9T0uyaWlpbFp06Yux2pra1m2bBkvvfQSc+bM6fN+WVlZpKSkAFBVVcWOHTtwdXVlxYoVNvuqrKzk6NGj3HTTTQDcd9993HnnnQBdink//PDDPPdc17/DTz75hLvvvhs3N7drMi57UjNmyoiWXWYgPtivx3eVPYkP9ier5LLNd6iKogyebG2l/q9/xfv22xHtsxmesbG0FBZirq93cHTOLTExkaKiIoqLizEajaSlpbF8+fJu7U6ePInBYGDu3LnWY0ajkbvvvpvVq1dz77339ut+xcXFlJSUUFJSQnJyMps3b2bFihU99uXv709NTQ2FhYUA7Nq1y1qo+9y5c9Z227dv71bAu/N+uGstLntTAzNlxKqsa6H0UuOAljE7JIT4c6G2Bb2haQgiU5TrV+ORHCy1tXgnzbMe89TpQEqVaLYPrq6ubNy4kcWLFxMREcHKlSuJiorihRdeYPv27dZ2qamppKSkdHlD+sknn3DgwAG2bdtmTQGR2z5LuWHDBrRaLXq9nujoaB566KFe4+ipL1dXV7Zs2cI999xDTEwMH374Ia+99pr1HlFRUcTExLBhwwa2bdtm7a+kpITy8nJuv/32Lve5VuKyNzFSZwwSEhJkVlaWo8NQHOibE+d59MNs/vSzucQHBwzo2vyztSzdcJC379OxInbyEEWoKL2rrT0GSHx9ox0dit1ceOVVDB99xMxD3+EyejQA5ro6Cm+8icDH1hG0bp2DI7StoKCg22yKogyWre8nIUS2lDKhr2vVjJkyYh0pM+CmEURNGviTleETfPAZ5aoSzSoOlV/wLMePP3lNLanX79uH1003WQdlABofH0aFhakHABSlH9TATBmxjpQauGHyGDzcBv6EjMZFEBvsT3apYQgiU5S+GY2XaWgopKm5jIaGQkeHYxctxcUYS0q6LGN28IyNpenoUaRF5Q9UlN6ogZkyIhlNFo7qa/pVuLwnCcH+nLxQR01Tqx0jU5T+qa7+Pg9SZeUuB0ZiP/Xp+wDwmTev2znP2FgsdXUYT58e3qAUZYRRAzNlRDpxtgajyTKojf8dEkL8kfL7XGiKMpwM1YdxcfHAx+cGKquukYHZvn2MmjkTt8nd92166mIAaMzJGe6wFGVEUQMzZUQ6UlYNQNxVDMx0U/zQuAiVaFZxiOrqDMaMiWX8uKXU1R2nufmso0O6KuaaGhqzs/FOSrJ53j0kBI2fH0256slMRemNGpgpI9KRUgOT/TwZ7+sx6D683F25YZIvWSVqxkwZXq2tNdTX/x0/v5sICloEQGXVbgdHdXW+z/Y/z+Z5IUTbPjM1Y6YovVIDM2XEkVKSVXr5qpYxO8QHB5BbXo3RpDYkK8OnbX+ZxN8vES+vaXh5hY34fWb1+/ahCQjAY/bsHtt46nQYi4sxGdSboZ7s3LmT8PBwwsLCeOWVV7qdX79+vTWH18yZM/Hz8wPaamfGx8ej0+mIiorit7/9LQCNjY0sW7aMWbNmERUVxfPPP2/t68CBA8TFxeHq6spnn33W7V61tbVMnjyZxx57rM++ysrKSEpKIjY2lujoaHbs2AG05Qrz9PS0xvzTn/4UgLq6OusxnU5HYGAgTz311IiOy26klCPyIz4+XirXJ72hUQY/95Xc9m3xVfe1I++sDH7uK3mk9PLVB6Yo/VRY+LLcs3eWNJmapJRSFp16Te7ZO0MajdUOjmxwLK2t8u833iQrnv+XXtvVHz4s88Nnydr09OEJbADy8/MdHYI0mUwyNDRUnj59Wra0tMjo6Gh54sSJHttv2LBBrl27VkopZUtLi2xubpZSSllXVyeDg4NlRUWFbGhokHv37rW2ueWWW+SOHTuklFIWFxfLo0ePygceeEB++umn3fp/4okn5KpVq+S6deuklLLXvh5++GG5efNmKaWUJ06ckMHBwdZ7REVF9fm1x8XFyf3794/ouDqz9f0EZMl+jG/UjJky4hwpHXjh8p7Eh7T1odJmKMPJUH2YMb4xaDRtS/FBQQuR0kzVpXQHRzY4jUeOYKmpwdvG05ided5wA2g0Kp9ZDzIyMggLCyM0NBR3d3dSUlL44osvemzfuZyQu7s7o0aNAqClpQVLe1oSLy8vktr3/bm7uxMXF4derwcgJCSE6Ohom8XOs7OzuXDhAosWLbIe660vIQS1tbUA1NTU9Fjj05aioiIuXrzIrbfeOmLjsidVxFwZcbJLDXi6aZg1weeq+xrn40HwWC8ySy7z0K2hdohOUXpnMtVRV5dPSMjPrMd8fWbj7j6OqsrdTJxg/9p7Q61+336Emxujb76513YuXl54zJrl9AXNz//3f9NS8He79jkqYhYT/vVfe21TUVHBlClTrK+1Wi2HDx+22ba0tJTi4mLmz59vPVZeXs6yZcs4deoUr732WrdBSHV1NV9++SVPPvlkr3FYLBaefvppPvzwQ/bs2WOzzZV9vfjiiyxatIh33nmHhoYGdu/+fs9kcXExsbGx+Pr68tJLL1kHOh1SU1O57777+qx57Kxx2Vufwz4hxO+FEBeFEMc7HftYCJHb/lEihMhtPx4ihGjqdO63na6JF0IcE0KcEkJsEO1fqRAiQAixSwhR1P7n1U+DKNe0I2UGYqaMwVVjn3ct8e2JZuU1lH1dcV7V1VmABX+/m6zHhHAhKOgOLl3ej9nc4rjgBqk+PR2vG29E4z26z7aesbE05eUhTaZhiGxksfUzqKdBQVpaGsnJyWg03yfYnjJlCnl5eZw6dYr333+fCxcuWM+ZTCZWrVrFE088QWho729CN2/ezNKlS7sMEjuz1VdqaioPPvgger2eHTt28MADD2CxWJg4cSJlZWXk5OTw5ptvcv/991tnsDp/Lf0pJO6scdlbf2bMtgEbgQ86Dkgp7+v4XAjxBlDTqf1pKaXORj+/AR4BDgE7gDuBr4HngT1SyleEEM+3v35uYF+Gcr1oNJo4cbaWn95uv9mthOAA/vdIBSWXGpkW2PcvFkW5GtXVmQjhypgxsV2OBwUupKLijxgMfyMw0HbKCWdkLCnBWFyM//3396u9p06H4Q9/oPnkSTyjooY4usHpa2ZrqGi1WsrLy62v9Xp9j0tvaWlpbNq0yea5SZMmERUVxcGDB0lOTgbgkUceYcaMGdaN7L357rvvOHjwIJs3b6a+vh6j0Yi3t7f1YQRbfb377rvs3LkTgLlz59Lc3ExVVRXjxo2zLrHGx8czffp0CgsLSUhoKxl59OhRTCYT8fHxIzYue+tzykFKeQCwmeipfdZrJZDaWx9CiImAr5Tyu/YNcB8AHfP1PwTeb//8/U7HFaWbPH0NZou0y/6yDont+8xUPjNlOBiqM/D1mY1G49XluL//HDQabyor/5+DIhucun37AHrMX3Ylr9i29+3OvpzpCImJiRQVFVFcXIzRaCQtLY3ly5d3a3fy5EkMBgNz5861HtPr9TQ1NQFgMBj49ttvCQ8PB+CXv/wlNTU1vP322/2K46OPPqKsrIySkhJef/11Vq9ebR389NTX1KlTrcuLBQUFNDc3ExQURGVlJWazGYAzZ85QVFTUZcau8z65kRqXvV3tWtCtwAUpZVGnY9OEEDlCiP1CiI4F28mAvlMbffsxgPFSynMA7X+O6+lmQohHhBBZQoisysrKqwxdGYk6svTHTrHfwGx6kDdjPN1UPjNlyJnNjdTVHcPP/6Zu51xc3AkcO4/Kqj1IaXZAdINTn76PUTNm4K7tnu3fFtdJk3ANClIPANjg6urKxo0bWbx4MREREaxcuZKoqCheeOEFtm/fbm2XmppKSkpKl2XOgoICbrrpJmJiYrj99tv5xS9+wezZs9Hr9bz88svk5+cTFxeHTqdj69atAGRmZqLVavn000959NFHiepjBrO3vt544w22bNlCTEwMq1atYtu2bQghOHDgANHR0cTExJCcnMxvf/tbAgICrH1+8skn3QZA10pcgyX6s69GCBECfCWlvOGK478BTkkp32h/PQrwllJeEkLEA38GooBw4H+klHe0t7sVeFZKeZcQolpK6depT4OUss/fugkJCTIrK6ufX6ZyrXjo/UzOVDWw9+l5du33J9syKbnUwB4796sonV26/Fdyc9egi/k9Y8fe3u38hQtfcfzEk8THfYyfX4IDIhwYc20thT+4mbFr1zLu6Z/3+zr9E0/SnJ9P2G7nyd1WUFBARESEo8NQrhG2vp+EENlSyj7/Yw96xkwI4Qr8CPi445iUskVKean982zgNDCTthkybafLtUBH/ZEL7UudHUueFwcbk3Jtk1KSXWq4qsLlPYkP8ed0ZQOXG4x271tROlQbDiOEhjFjbO9bGTv2doRwGzG1Mxv++lcwmfq9jNnBMzaWVr2e1ovqx72iXOlqljLvAP4upbQuUQohgoQQmvbPQ4EZwJn2Jco6IcSc9n1pq4GO5CzbgTXtn6/pdFxRuiiuasDQ2GrX/WUdEkPaprBVPjNlKBmqM/DxjsLV1dvmeVdXH/z951BZuWtEPCVcl74Pjb8/njHRA7quo6C52memKN31J11GKvAdEC6E0AshftJ+KoXum/5vA/KEEEeBz4CfSik7dlT/DNgKnKJtJu3r9uOvAAuFEEXAwvbXitKNPQqX92T25DG4a1zUAwDKkDGbm6mtzcPP/8Ze2wUFLaKpqZSGxlPDFNngSJOJ+gMH8L7tNkSnlA394REVhXBzUwXNFcWGPtNlSCltPpYgpXzQxrE/AX/qoX0WcION45eABX3FoSjZpQZ8PFwJC7I923A1PNw0zNaOIUvNmClDpKY2BymNXfKX2RIUuICTJ/+NqspdeI+eMUzRDVxTbm5btv8BLmMCuLi743HDDaqguaLYoEoyKSPGkVIDcVP9cXEZmizMCcH+HNPX0Nw6cp6IU0aOakMGIBgzpve9v6NGjcfXV+f0Rc3r0tPBzY3Rt/Se7b8nnjodzcePYzGqfZ2K0pkamCkjQm1zK4UX64Zkf1mHhJAAjGYLxypq+m6sKANkqD6Mj3ckbm6+fbYNClxIbV0ezc3nhiGywanft5/RiQlovAc3g+0Zq0O2ttKSn2/nyBRlZFMDM2VEyC2rRkr7FC7vSUffmWqfmWJnFksLtbW5fe4v6xAUtBCAqirb9QAdzVhWhvH0abznDb5CgaeuLdFso8pn1sXOnTsJDw8nLCzMmjy1s/Xr16PT6dDpdMycORM/P78u52tra5k8eTKPPfYYAI2NjSxbtoxZs2YRFRXF888/b21bVlZGUlISsbGxREdHs2PHDgBKSkrw9PS03uenP/0pAHV1ddZjOp2OwMBAa5b9AwcOEBcXh6urK5999llV16dzAAAgAElEQVS3uK/luOxNFTFXRoTsUgMuAmKm+PXdeJACRrszPWg02SrRrGJnNbV5WCwt+Pv1b2A2evR0vLxCqazchVb7j0Mc3cDVp6cD4J00b9B9uI0bh9vkyerJzE7MZjPr1q1j165daLVaEhMTWb58OZGRkdY2b731lvXzd955h5wr9un927/9G7ff3jVH3i9+8QuSkpIwGo0sWLCAr7/+miVLlvDSSy+xcuVKfvazn5Gfn8/SpUspKSkBYPr06eRe8W/j4+PT5Vh8fDw/+tGPgLYM+9u2beP111+3+bVd63HZk5oxU0aEI2UGwif44j1qaN9LJAQHkF1mwGJx/lQFyshRbTgMgJ9fYr+vCQq8A0P1IVpba/tuPMzq9u3DPWw67j0Uk+4vz9hYmnJyRkRqkOGQkZFBWFgYoaGhuLu7k5KSwhdf9JxB6sqyQdnZ2Vy4cIFFixZZj3l5eZHU/oCGu7s7cXFx6PVtWa6EENbC3TU1NT3W5bSlqKiIixcvcuutbQV+QkJCiI6OxsWl+7BCxTUwasZMcXpmiySnrJoVsUPzn6CzhBB/Ps4q53RlPTPG+wz5/ZTrQ3V1Bt6jw3Fz6/9SfFDQQkrLfselS/uYMKF7vURHMdfV0ZiZxdi1D151X546HbVffYXp7FncJvevpNNwOPhJIVXl9XbtM3CKN7eunNlrm4qKCqZ0GuxqtVoOHz5ss21paSnFxcXMnz8fAIvFwtNPP82HH35orQ15perqar788kuefPJJAF588UUWLVrEO++8Q0NDA7t377a2LS4uJjY2Fl9fX1566SXrQKdDamoq9913X5eyULZcL3HZk5oxU5xe4YU66ltMQ7q/rENCe6LZkZI2Q1osjg5B6YPF0kp1zZF+7y/r4Ourw9090OmqAFiz/c+bd9V9ebYXNG9Uy5kANmcOexpgpKWlkZycjKY9h9zmzZtZunRpl4FdZyaTiVWrVvHEE09Yi3Wnpqby4IMPotfr2bFjBw888AAWi4WJEydSVlZGTk4Ob775Jvfff791pqjz/ftT5Pt6iMve1IyZ4vQ6CpfHDUEppiuFjPVi7Gh3Mksus+rGqUN+v6uR8cVnHNnxBT/59RbcPDwcHY7Sg7q6Y1gsTfj1kb/sSkK4EBh4BxcufInF0oKLy6ghinBg6vftQ+PnZ928fzU8wsMRnp405eQyZtkyO0RnH33NbA0VrVZLeXm59bVer+9xuSwtLY1NmzZZX3/33XccPHiQzZs3U19fj9FoxNvb2/oAwSOPPMKMGTOsm+IB3n33XXbu3AnA3LlzaW5upqqqinHjxjFqVNv3W3x8PNOnT6ewsJCEhLZUL0ePHsVkMhEfb7u0WGfXS1z2pGbMFKeXXWog0NudqQFeQ34vIQQJIf5OX5qpsrSYbz/+kIZqA2UnVPZ0Z2YwZADgP4D9ZR2CghZiNjdw2fCdvcMaFGk2U7//AN63Dzzbvy3C1RXP2bPVAwDtEhMTKSoqori4GKPRSFpaGsuXd1/GPnnyJAaDgblz51qPffTRR5SVlVFSUsLrr7/O6tWrrYOMX/7yl9TU1PD222936Wfq1KnWZbyCggKam5sJCgqisrISs7ktn+OZM2coKiqyzhpB971tvbke4rI3NTBTnF5HYtm+9gzYS0JwAKWXGrlY1zws9xsos8nEzt+8jYe3D24enpzJznR0SEovqqsP4+UVhrt74ICvDfCfi0Yz2mmSzTbl5mKurrbLMmYHz9hYmgsKsDQ22q3PkcrV1ZWNGzeyePFiIiIiWLlyJVFRUbzwwgts377d2i41NZWUlJR+/UzU6/W8/PLL5OfnExcXh06nY+vWrQC88cYbbNmyhZiYGFatWsW2bdsQQnDgwAGio6OJiYkhOTmZ3/72twQEBFj7/OSTT7oNgDIzM9FqtXz66ac8+uijREVFXTdx2ZsYqU/DJCQkyKysLEeHoQyxqvoWEl7azb8smcWjt08f0LUXL15k1KhRjBkzZkDX5ZQZuHvz3/jNj+NYMnvigK4dDof+92O+/fhDlj/9rxQc3Me5Uyd5ZPPQ/IBQro7FYuLAwTgmTPghs8L/a1B9HDv+ONXVmdxy898QwrHvpS++8QaX3tvGzO/+hsbHPg/H1KWno//ZPzP1g/cZfePA9uHZU0FBAREREQ67v3JtsfX9JITIllL2XvoDNWOmOLmcQRYuN5lMbNu2jS+//HLA94yaNIZRri5kOmE+s6qyEr77LJXwH9zGjBt/QGhcIvWXL1FZWuzo0BQb6uvzMZsb8Otn/jJbggIXYjRWUlvr+CXruvR0vBIT7DYog+8TzaqC5orSRg3MFKeWXWrATSOYPXlgs14FBQU0NjZSWlqKyWQa0LXuri7opviRXepcFQAsZjM7f/M2o0aPZv7aRwGYFtv25utMdoYjQ1N6YKhuS3XQV+Hy3owdOw8hXB2+nGksL8d46jQ+dlzGBHD198d92jRV0FxR2qmBmeLUjpQaiJo0Bg+3gW00zsrKQghBa2srFRUVA75vQog/x8/W0mgc2KBuKGV++b9cOHOKO37yM7x82waqo/38mRA2kzNH1D4zZ1RtyMDTM4RRowb/1Jabmy/+fnMcnjajPn0fAN5Jgy/D1BNPnY6m3FyVaFZRUAMzxYkZTRaO6qsHnL+ssrKS0tJS6xNLgymZkRASgNkiyS2vHvC1Q+GSvozvPv2ImXNuYeacW7qcC41L5NzpQhqqnW/p9XompZnqmsx+l2HqTVDQQhobz9DQcNoOkQ1O/b503KdPx32q/dPIeMbqMBsMtJaW2r1vRRlp1MBMcVr552ppMVkGPDDLzs7GxcWFH/zgB0yYMIHi4oHvv2p7ChSynGCfWccSprunFwv+6afdzofG3QhSUpyb7YDolJ7U1/8dk6kOP//BL2N2CAxcAOCw5UxzfT0NmVl4z7u978aDoAqaK8r31MBMcVpHSgeeWLa1tZXc3FxmzZqFt7c306ZNo7y8nNbW1gHde4ynG+HjfZyiAkDWV59z/lQh8//pp3iN6V7EfVxIKN7+AZw5ovaZORNDdUf+squfMfPwmIivT7TDljMb/vottLbiMwTLmACjwsJw8fZW+cwUBTUwU5xYdpmByX6eTBjT/6z2+fn5NDc3WzNBh4SEYDabrUVoByI+2J8jpQbMDixofqminL99+hEzbvwB4XNvtdlGCMG0uERK83IwmwY2AFWGTrXhMB4eU/DwsE+N16CghdTW5tLScsEu/Q1EfXo6mjFj7JLt3xbh4tK2z0w9AMDOnTsJDw8nLCzMmvC0s/Xr16PT6dDpdMycORM/v+/frGk0Guu5zolpf/KTnxATE0N0dDTJycnU17fVAd22bRtBQUHWazrydaWnp1uP6XQ6PDw8+POf/wzAxo0bCQsLQwhBVVVVt/gyMzPRaDR89tlnAOTm5jJ37lyioqKIjo7m448/trbds2ePNVfYLbfcwqlTp5w6LmjLlRYZGUlUVBT3339/z/+QV0NKOSI/4uPjpXJtm/Pfu+VjfzwyoGu2bt0qf/3rX0uz2SyllLKpqUm++OKLcs+ePQO+/+dH9DL4ua/kiYqaAV9rD2azSX70f34uN/5Tiqw3XO61bVHmIfn6ymWyJC9nmKJTemOxmOW+/XHyxIln7NZnXd1JuXtPqCzXf2S3PvvDYjLJk3PmSv0v7Pe12HLxnY0yf1aENNXWDul9epKfn++Q+3ZmMplkaGioPH36tGxpaZHR0dHyxIkTPbbfsGGDXLt2rfX16NGjbbarqfn+Z9j69evl//zP/0gppXzvvffkunXreo3p0qVL0t/fXzY0NEgppTxy5IgsLi6WwcHBsrKyslv8SUlJcsmSJfLTTz+VUkp58uRJWVhYKKWUsqKiQk6YMEEaDAYppZQzZsyw/r1v2rRJrlmzxqnjKiwslDqdTl6+3Pbz+MKFCz3GZ+v7CciS/RjfqBkzxSmdrW7iXE0z8VO7L9315OLFi5SXlxMfH4+LS9u3toeHB5MmTRrUPrOOvW2OSptx5C9fcK7oJPP/6aeM9ut9OTf4hhg0bm7q6Uwn0dBQhMlUPeDC5b0ZPXoGnp7BVA3zPrOmo3mYDQZ8kuYN6X08Y3UgJU15eUN6H2eWkZFBWFgYoaGhuLu7k5KSwhdffNFj+/6WIPL19QXaJmKampoGlIz6s88+Y8mSJXh5tZXEi42NJSQkxGbbd955h3vuuadL7ciZM2cyY8YMACZNmsS4ceOorKwE2mb7O4qQ19TU9FgX1Fni2rJlC+vWrcPfv+3nsb1rZHZQRcwVp2QtXD6Ajf9ZWVnWqfzOQkJC+O677zAajbi7u/e7P62/JxN8PcgsMfDA3JB+X2cPl8/q+fbjPxCWOIdZP7itz/ZuHh5MjYrmTHYG81Y/pKoAOJg98pddSQhBUNBCysvfx2Sqw9XVfklee1Ofng6uroy+5Za+G18Fz5gYEIKmnFy8b755SO/Vl/Rtv+Ni6Rm79jkuOJSkBx/ptU1FRQVTpkyxvtZqtRw+fNhm29LSUoqLi5k/f771WMc2DldXV55//nlWrFhhPbd27Vp27NhBZGQkb7zxhvX4n/70Jw4cOMDMmTN56623utwf2oql//znP+/z66uoqODzzz9n7969ZGbafoOYkZGB0Whk+vS2Ki5bt25l6dKleHp64uvry6FDh5w6rsLCQgBuvvlmzGYzL774InfeeWefMQyUmjFTnFJ2qQEPNxciJvr2q73RaOTo0aNEREQwevToLuemTZuGxWKhrKxsQDEIIYh3QEFzi8XMN7/5Na7u7tzx0Lp+D7JC426k+sI5DOcGnrdNsa9qQwajRk3Ew0Nr136DAhciZSuXLu23a7+9qd+Xjld8PBrf/v1fHCyNtzejZsy4rh8AkDbyuPX0/z8tLY3k5GQ0nYrJl5WVkZWVxR//+EeeeuopTp/+Pr3Ke++9x9mzZ4mIiLDup7rrrrsoKSkhLy+PO+64gzVr1nS5x7lz5zh27BiLFy/uM/annnqKV199tUs8V/b1wAMP8N5771lXNN566y127NiBXq9n7dq11oGWs8ZlMpkoKipi3759pKam8tBDD1Fdbf+USmrGTHFKR0oNxGj9cNP0773DiRMnaGlpsW7672zq1Km4uLhQXFxMWFjYgOJICPbnL3nnOFvdxCQ/zwFdO1g5X3/F2cICljz2dJ9LmJ2FxiWy5/e/4Ux2BgGT7DsgUPpPSomhOoOxAbfafeZyzJhY3NzGUlm5i/Hj/8Gufdti1OtpKTrFuOfvGfJ7QVtB89q//AVpsSBcHDdv0NfM1lDRarWUl5dbX+v1+h6X99LS0ti0aVOXYx1tQ0NDmTdvHjk5OdZZIGh7OOC+++7jtddeY+3atYwdO9Z67uGHH+a5557r0t8nn3zC3XffjZubW5+xZ2VlkZKSAkBVVRU7duzA1dWVFStWUFtby7Jly3jppZeYM2cO0JZv8ujRo9x0U9us8n333WedfXLWuLRaLXPmzMHNzY1p06YRHh5OUVERiYmJfcYxEGrGTHE6za1mTpytHVD+suzsbAIDAwkODu52zt3dHa1WO6h9ZokhAQDDljbDcK6Cv6Z9QGj8jUTcMm9A1/oGjSNwaojaZ+ZgjY2naW29ZNf9ZR2E0BAUuICqS/uwWFrs3v+VOrL927sMU088dTos9fW0dHoK7nqSmJhIUVERxcXFGI1G0tLSujxd2eHkyZMYDAZrEm0Ag8FAS0vb90RVVRXffvstkZGRSCmtTxVKKfnyyy+ZNWsW0DZb1GH79u3dim73dw8bQHFxMSUlJZSUlJCcnMzmzZtZsWIFRqORu+++m9WrV3Pvvfda2/v7+1NTU2NdHty1a5f1/s4a14oVK0hPTwfa/o4LCwsJDQ3tVxwDoQZmitPJ09dgssh+5y87f/48er2e+Pj4HmcoQkJCOHfuHM3NzQOKZdYEH7zcNWSVDP0DANJi4Zvf/hqNmysLB7CE2VloXCL6v5+guaF+CCJU+sOe+ctsCQpahNlcj8Fge++RPdWnp+M+bRruPWyqtjev2I6C5tfncqarqysbN25k8eLFREREsHLlSqKionjhhRfYvn27tV1qaiopKSldfkYUFBSQkJBATEwMSUlJPP/889aB2Zo1a5g9ezazZ8/m3LlzvPDCCwBs2LCBqKgoYmJi2LBhA9u2bbP2V1JSQnl5Obff3jWp8IYNG9Bqtej1eqKjo3nooYd6/Zo++eQTDhw4wLZt26xpLnJzc3F1dWXLli3cc889xMTE8OGHH/Laa68Ne1y/37aNiOhoovsR1+LFixk7diyRkZEkJSXx2muvdZndsxdha017JEhISJBZWVmODkMZAr/Zd5pXd/6dI/+2kIDRfW/W/8tf/sKRI0d4+umnrU/oXKm4uJj333+fVatWER4ePqB4/nHrYS43GNnxpO08YvZy5OvtpG/7HXf+83qibl8wqD4q/p5P2r8/y7Inn+3XQwOK/R0/8RQGw2FuuflvQ/IQhtncwsG/JjBhwt3MCv9Pu/dvvU99A4Vz5xLwwAOMf/aZIbtPZ1JKin5wM97z5jHpf/57WO7ZoaCgoNvMjHLtu9DSyvmWViK9PXCz4/K5re8nIUS2lLL7fpsrqBkzxelklxoIDRzdr0GZ0WgkLy+PqKioHgdl0LY3QKPRDDptxt/P11LXPHTJW6vPn+Ng6vtMi00g8rb5fV/Qg4kzw/Hw9qFYLWc6hJSSakMG/n43DtmTsRrNKAICbqOqcjdSWobkHgAN37Zl+x+qMky2CCFUolllWNWbzXhohF0HZVfLeSJRFNp+sR0pM/Q7Tcbx48dpaWkhPj6+13Zubm5MmTJlUAXNE0MCsEjIKRuagubSYuGb//trNBpXFj7y2FX9Qndx0TAtNoEzudlYLGY7Rqn0R1NTKS3GC/gN0TJmh6CghbQYL1Bbd2zI7lG/bx8uY8bgFRc3ZPewxTM2FmNJCSaD48uhKdc2s5Q0mC349PDEpqOogZniVEouNXK5wdjvjf9ZWVkEBQUxderUPttOmzaN8+fP09jYOKCYdFP9cBEM2T6z3F070OcfZ97qh/AJCLzq/kLjEmmuq+VcUaEdolMGorp9f9lQbPzvLHBsEkJohqyouTSbqd+/H+9bb0W4Du/D+566GOD63WemDJ9GswUpwdtVDcwUpUcDKVx+9uxZzp492+um/86mTZsGMOBZM+9RrkRO8h2SJzOrL5zn4EfbCImJI2reHXbpMyQmDuHiooqaO4Ch+jBubgGM9hpYWpaBcnMbg5/fTUM2MGvKy8N8+TLew/Q0Zmees2eDRkNT7tFhv7dyfakzmRECRvczLdNw6TMaIcTvhRAXhRDHOx17UQhRIYTIbf9Y2uncvwghTgkhTgohFnc6fmf7sVNCiOc7HZ8mhDgshCgSQnwshOh/anblmpNdZsBnlCszxnn33TY7G1dXV2JiYvrV96RJk3BzcxvUcmZCcAA5ZdW0mu23p0daLPy//7sB4SJY+MjjdtuT5DHaG+2sKJU2wwGqDRn4DeH+ss6CghbS2HiKhgb7ZqgHqN+3HzQavG8d2mz/trh4euIREaH2mSlDrs5swUvjgsbJKqX0Z5i4DbBVc+AtKaWu/WMHgBAiEkgBotqv2SyE0AghNMAmYAkQCaxqbwvwantfMwAD8JOr+YKUke1IqYHYYH9cXHr/j9LS0sKxY8eIiorC07N/iV9dXV2ZOnXqoB4ASAjxp6nVTMG52gFf25O8PTspP5HH7Q88hG9gkN36hbblzKqyEmorL9q1X6VnTU16mlvODlmajCsFBbbNsFZV2X/WrD69Pdv/mDF277s/PHU6mo4dQ5pMDrm/cu1rtUianXB/GfRjYCalPAD0d3PND4E0KWWLlLIYOAXc2P5xSkp5RkppBNKAH4q2t5Xzgc/ar38fWGGjX+U6UNvcyskLdcT3Yxnz2LFjGI1Gm5n+ezNt2jQqKyuprx9Ynq+E4LZEs5kl9lnOrLl4gf1/eI/g6Fhmz19klz47C41vGxyoWbPhU91eH9PP3371MXvj4TEJH58oKqt227Xf1ooKWgoLHbKM2cEzVodsaqL55EmHxeAoO3fuJDw8nLCwMF555ZVu59evX2/NBzZz5kz8/Pys58rKyli0aBERERFERkZ2Wx14/PHH8fb+fjXizTffJDIykujoaBYsWEBpaan13LPPPktUVBQRERE88cQT1nJR8+bNIzw83BrDxYsX+4zrzjvvxM/Pj3/4B9vVKhwRV73ZzD//6IeEjw+yS1z2dDULq48JIfLalzo7fpNOBso7tdG3H+vp+FigWkppuuK4TUKIR4QQWUKIrI4q8Mq142h5NVJCXLBfr+2klGRlZTFu3Di02oGVHgppT5Q50OXMCWM80Pp7kl169Q8ASCnbljAFLHrUfkuYnflPnIzf+Ilqn9kwMlRn4Orqh/fomcN2z6DAhdTU5NDSYr+fh3X79gHgnTTPbn0OlJeuPdFszvX1AIDZbGbdunV8/fXX5Ofnk5qaSn5+fpc2b731Frm5ueTm5vL444/zox/9yHpu9erVPPPMMxQUFJCRkcG4ceOs57KysrrVdYyNjSUrK4u8vDySk5N59tlnAfjb3/7Gt99+S15eHsePHyczM5P9+7+vz/rRRx9ZY+i4R29xPfPMM3z44Yc2v2ZHxVVvMvPgk0/xwQcfXHVc9jbYgdlvgOmADjgHdJSqt/UbRg7iuE1Syt9JKROklAlBQfZd+lEcL7vUgBCgm9L7wOzs2bOcP3+ehISEAQ9qJk6cyKhRowa3nBnsT1aJwWah4YE4tucbyo4f5bYf/xO+geP6vmAQhBCExiVSdiKP1gFWO1AGp21/WQJCDN9G4qCgRYCkqmqP3fqsT9+He0gIo9oflnEE10mTcB037rp7MjMjI4OwsDBCQ0Nxd3cnJSWFL774osf2nUsT5efnYzKZWLhwIQDe3t7W3I5ms5lnnnmGX/3qV12uT0pKsraZM2cOer0eaPv50dzcjNFopKWlhdbWVsaPH9/vr+PKkkkLFizAx8enWztHxSWlpM5sYeGCO/D19b3quOxtUM9BSykvdHwuhNgCfNX+Ug9M6dRUC5xt/9zW8SrATwjh2j5r1rm9cp3JLjUQPt4HH4/eC9NmZWXh5uZGdHT0gO+h0WgIDg4eXKLZkAD+nHuW8stNTB3bczLb3tRWXWT/H95l6g3RRN9ha+um/YTG3ciRr7dTduIo0+OHZ3ntetXcfI6m5jK02geG9b6jR8/E02MqlVW7mDw55ar7M9c30Hj4MP4//rEdohs8IQSesbEOewCg+svTGM822LVP90mj8btreq9tKioqmDLl+1+VWq2Ww4dtl94qLS2luLiY+fPbElIXFhbi5+fHj370I4qLi7njjjt45ZVX0Gg0bNy4keXLlzNx4sQe7/3uu++yZMkSAObOnUtSUhITJ05ESsljjz3WJYv92rVr0Wg03HPPPfzyl7/s8gb5yrh646i4jBZJq0Xi7W77TdRA47K3Qb21E0J0jvZuoOOJze1AihBilBBiGjADyAAygRntT2C60/aAwHbZNvWQDiS3X78G6PntgXLNslgkuWXVfeYva25u5vjx49xwww14eHgM6l7Tpk3j8uXL1NTUDOi6xJC22LIGuZzZtoT5DtIiWfTok0P+5J42Mgo3D0/OZKt9ZkNtuPKXXUkIQVDQQi5f/hsm09XXR2347m/I1la8k5LsEN3V8dTpaK2ooPXi9fMAi63Z+J5+TqSlpZGcnIymffO6yWTi4MGDvP7662RmZnLmzBm2bdvG2bNn+fTTT3n88cd7vO8f/vAHsrKyeOaZttJbp06doqCgAL1eT0VFBXv37uXAgQNA23LhsWPHOHjwIAcPHuy2RHllXD1xZFx15rbk27Y2/g8mLnvrc8ZMCJEKzAMChRB64N+BeUIIHW3LjiXAowBSyhNCiE+AfMAErJNSmtv7eQz4BtAAv5dSnmi/xXNAmhDiJSAHeNduX50yYhRdrKeuxdRn/rK8vDxaW1sHvOm/s877zPqbagNg5jgffDxcySwx8KO4ge1tAzievovSvBwW/OSfGTOu/9Pvg6VxdSMkJpYzRzKQUg5LCofrlaH6MK6uPvh4D3+txcCghZSVv8ulywcYP25p3xf0oj59Hy6+vnjFxdopusHrXNDcbZH9H5DpTV8zW0NFq9VSXv79dmy9Xs+kSZNstk1LS2PTpk1dro2NjSU0NBSAFStWcOjQISZMmMCpU6cIC2vLrdfY2EhYWBinTp0CYPfu3bz88svs37+fUaNGAfD5558zZ84c68b3JUuWcOjQIW677TYmT27bBu7j48P9999PRkYGq1ev7jGunuTk5DgsrnqzBTcXgbuNp/8HE5e99eepzFVSyolSSjcppVZK+a6U8gEp5WwpZbSUcrmU8lyn9i9LKadLKcOllF93Or5DSjmz/dzLnY6fkVLeKKUMk1LeK6Vssf+XqTi77Pbkrb3NmEkpyc7OZsKECT3+sOqP8ePH4+npOeDlTBcXQXyw/6AeAKitqmTfB1uZEjmbmCFewuwsNO5G6g2XuVhi/1xXyveqqzMYMyaBtsxAw8tvTBxubgFXnWxWWixt2f5vuQXh1vt2guEwKjIS4e5+XT0AkJiYSFFREcXFxRiNRtLS0li+fHm3didPnsRgMDB37twu1xoMBjoejNu7dy+RkZEsW7aM8+fPU1JSQklJCV5eXtZBRk5ODo8++ijbt2/v8qDA1KlT2b9/PyaTidbWVvbv309ERAQmk4mqqioAWltb+eqrr7jhhht6jasnjopLSkm9yYyPxsXmm9XBxGVvzpXuVrluZZcaGDvaneBe9m7p9XouXLgwqE3/nbm4uBASEjLoBwAKL9RT3Wjs9zVSSnZt2YjFYmbRT59EDGOx3Gm6eBBCPZ05hFpaLtLYWDxs+cuuJISGwMD5XLqUjsXSOuh+mo8dw0W2JkQAACAASURBVHzpklMsYwK4uLvjERV1XT0A4OrqysaNG1m8eDERERGsXLmSqKgoXnjhBbZv325tl5qaSkpKSpefgxqNhtdff50FCxYwe/ZspJQ8/PDDvd7vmWeeob6+nnvvvRedTmcdBCYnJzN9+nRmz55NTEwMMTEx3HXXXbS0tLB48WKio6PR6XRMnjy5yz1sxQVw6623cu+997Jnzx60Wi3ffPONw+JqtFgwt5dhsldc9iau9gkzR0lISJBZWVmODkOxk6TX9xE2zpstq3teovzzn/9Mfn4+Tz/99FVPIR8+fJivv/6aJ598En///tXlBDh05hIpvzvE7x9MYP6s/i1HHt+3m29+8zbz1z5K7J13DTbkQfvj/3kaieTHL7857Pe+Hly48BXHTzxJQsL/Msa3/0vj9lRZuZu8Y48Sq/uAgICbB9XHxbff5tKWrcz89q9o/Hp/Mnq4XPjVaxg+/JCZ2Vm4uA9tUZiCgoIuG8mVa9OFllbOt7QS6e2B2xC+Sbb1/SSEyJZS9rkPR82YKQ53qb6F4qqGXpcxm5qaOH78OLNnz7bLun5H3cyBzprFaP1wdRH9TjRbd7mKfe9vQRtxA7pFywYcpz2ExiVy/lQhDdX2r/WptOUv02hG4+Md5bAYAgJuwcXF86qWM+vT9+EVG+s0gzJoK2guW1tpPnGi78aK0g91ZjMeGjGkg7Kr5byRKdeNnLK2JH69bfzPy8vDZDIRHx9vl3sGBQUxevToAQ/MPN013DB5DNn9GJhJKdm9ZRNmk4nFw7yE2dm0uEQAinOzHXL/a13b/rI4XFwGlX3ILjQaD8aOvZXKql2DyrPXevYsLSdPOs0yZgfPjkSzqqC5YgdmKWl00jJMnamBmeJw2WUGXF0E0Vrbdfk6Mv1PmjTpqjb9dyaEICQkhJKSkgH/IksI9idXX02Lydxru/wDezlzJJNbV63Gb0LP+XCG2riQULz9A9Q+syFgNF6ioaEIfz/H54kLClxIS8t56uqODfhaZ8j2b4vbuHG4abWqoLliFw1mC7J9f5kzUwMzxeGySw1ETR6Dh5vt/yxlZWVUVlbabbasw7Rp06irq+PSpUsDui4hJACjycLxip4LmtcbLpP+/u+YPCvSIfvKOmurAnAjJUdzMJsGvzlc6a66ui1H3HDnL7MlMDAJITSDWs6sT9+HW/BU3B2Y7b8nnjodTTk5V11xQ1HqTWaEgNEa5x76OHd0yjWv1WwhT1/da+Hy7Oxs3N3duzz+bA+D3WfWsRcuq8R22oyOpzDNxlaHLmF2FhqfSGtzE/p8tVfHngzVh3Fx8cDXZ7ajQ8HNzR+/MYlUVg1sYGZpaKDx0CF85iU5Za47z1gdpspKTGdVURjl6tSZzXj9f/bOPC7qav//z8/MsAybgKCxKIsIIggDYmnlvpVbi2baXrd+t7p1W+417+32bbm3xbrdq5llm13LumpapqnZdQE1NRE3FHAHZN+XGWCY7fz+GJhEQBhkG5vn48ED5vM5n3NeH5hhzpz3+7zechnyXvg8v5Sef8ew85smo6Aard7UauHy2tpa0tLSiImJ6XQzP29vb9zd3a0uaO7r7kSIjysp2S3nmZ36OYkLh5O5ef4DePkFdILSq2dgdCwKB0d7OLOT+TW/rGt3DLYXH99J1NScpbY2q93X1Bw40OD2P67LdF0NjXlmtb8hPzM7nY/eZEJrFL0+vwzsEzM7PUxbxrLHjx/HaDR2zOk//xiUt74aJkkSISEhZGZmWh0mMRvNNi9oXlNZwa7/fIxf+BDibu3ZEOalODg5MyA6hvMNVQDsXD16fSUazeke8y9rCV8fcwHrktId7b5GnZiIzN0dl05OFegsnCMikJTK34yf2bZt24iIiCAsLIxFixY1O//cc8+hUqlQqVSEh4fj2bCLNjEx0XJcpVLh7OzM999/3+Tap59+2uKaD+b6kRMnTiQmJoZx48Y1Kcq9cOFCoqOjiY6OZu3atZbju3btIj4+nujoaB588EEMBgMAFRUV3HHHHcTExHD99ddz8uRJyzXvvfce0dHRREVFsWTJEsvx48ePM2rUKIYNG8bMmTOprjanh+h0Oh5++GGLX1lSQw4kwNq1a4mJiSEqKooXXnih3fcSMyyG2SMT2Pbd+i65l05FCGGTX8OHDxd2bJ8/fH1YjHpzR4vnTCaTWLp0qfjkk0+s71hXJ8SiICE+v/WKzY4cOSJeeeUVUVhYaFX3a5KzRdDCzeJcsbqJ3u//+Q+x+N7bRVlejvWau5ijP20R786dLkpzL/a0lGuC4uL/iR07Q0V5+cGeltKEXw7OEIdS5rarrcloFKdvulnkPvdcF6u6OrIeeFBcuHN2l46Rnp7epf23B4PBIEJDQ8X58+dFfX29iImJEWlpaa22X7p0qXj44YebHS8rKxNeXl6ipqbGcuzQoUPivvvuE66urpZjc+bMEStXrhRCCLFz505x3333CSGE2Lx5s5g0aZLQ6/VCo9GI4cOHi6qqKmE0GkVgYKA4ffq0EEKI//u//xOfffaZEEKIP//5z+LVV18VQgiRkZEhJkyYIIQQ4sSJEyIqKkrU1NQIvV4vJk6cKM6cOSOEECIhIUEkJSUJIYRYsWKFeOmll4QQQixbtkw89NBDQgghioqKRHx8vDAajaK0tFQMGDBAFBcXCyGEeOCBB8SOHTvadS8XqjXiYEFxl93L5bT0fAJSRDvmN/YVMzs9ypHsCuJbWS3Lzs6mrKysY6tlpzZDXQVcPAA1pa0263iemTdAE9uM0/v3cO7QL9x09/14+1tfS7OrCY03/x4vHLEXNe8MKiqTkckc8eghU9nW8PWdTFXVYXS61p/3jWhPnsRYWorbuHFdL+wqUKpUaE+dwlRb29NSupTk5GTCwsIIDQ3F0dGRefPmsXHjxlbbr169mvnz5zc7vn79em699VZcXMyVVIxGIwsWLOCdd95p0i49PZ2JEycCMH78eMtY6enpjB07FoVCgaurK7GxsWzbto2ysjKcnJwIDw8HYPLkyXz77bfN+hoyZAhZWVkUFRWRkZHByJEjcXFxQaFQMHbsWDZs2ACYSyWNGTPmin3169cPT09PUlJSuHDhAuHh4fj6+gIwadKkFq+5/F7GjBlDnSSjXx+PLruXzqTnjHfs/OYpqKojv0rLo60k/qekpODk5ERUVAeMO4+uAkd30Knh9I8Qf3+LzTw9PfH09CQrK4uRI0e2u/tBvq54uThwKKucuSMGUFNZwc7/fIzf4AiGT7/Ner3dgIdPP3wGBpN55BAjZt7Z03JsnsrKg3h4xCGXd00h447i6zOZzMz3KC3dhb//3Cu2VScmgkyG6+jR3aSuYyjjVGA0UnfyJK7Xd33o+Mcff6SwsLBT+7zuuuu49dZbr9gmLy+PAQMGWB4HBgZy8ODBFttmZ2eTmZnJhAkTmp1bs2YNzz//vOXxsmXLmDVrFn5+TW17YmNj+fbbb3nmmWfYsGGDZZd6bGwsr732Gs8//zy1tbUkJiYydOhQfHx80Ov1pKSkkJCQwPr16y1F12NjY/nuu++4+eabSU5OJjs7m9zcXKKjo/nb3/5GWVkZSqWSrVu3Wj5sR0dHs2nTJm677TbWrVvXpK+NGzcyb948cnJyOHz4MDk5OUyYMIFTp06RlZVFYGAg33//PTqdrs17eeXV15j82BPITfouu5fOxL5iZqfHOJJtNpZtKb+spqaGjIwMYmNjcbS2FEtFNlxIghufgj4DzatnVyAkJISsrCxMJlO7h5AkieFB3pY8s50rlqPX1jH18WeRyXpvcmlo/AhyT6WhrdH0tBSbxmBQo1Zn9Kr8skbc3Ibg7BzYLtsMTdJulPFxKKwoS9YTKGPNq5LXekFz0UL+Z2s7ZdesWcOcOXOQX5bMXlBQwIkTJ5g6dSoA+fn5rFu3jqeffrpZH++++y67d+8mLi6O3bt3ExAQgEKhYMqUKUybNo0bb7yR+fPnM2rUKBQKBZIksWbNGp577jmuv/563N3dUSjM6zt/+ctfqKioQKVS8f777xMXF4dCoSAyMpKFCxcyefJkbrnlFmJjYy3XfP7553zwwQcMHz4ctVpt+V//yCOPEBgYSEJCAs8++yw33ngjCoUCLy8vli9fzt13383o0aMJDg629HWlexl/y1QenDKBJx+4v8vupVNpT7yzN37Zc8xsn9c2pYmIl7YKncHY7NzPP/8sXnnlFVFUVGR9x7veEOKVPkJUXBRi60Ih/u4rhLa61ebHjx8Xr7zyisjLy7NqmOVJ50TQws3il8Qk8e7c6eLg9+us19rN5J5KF+/OnS4y9u3uaSk2TUnJLrFjZ6goK9vX01Ja5PSZf4hdiUOEXq9ptY0uP1+kRwwRpZ9+2o3KOs65W24VFx9/osv67w05Zvv37xdTpkyxPH7zzTfFm2++2WJblUol9u1r/vxbsmSJeOyxxyyPN2/eLPr37y+CgoJEUFCQkCRJDBo0qNl1arVaBAQEtDjW/PnzxZYtW5od/+mnn8Rdd93V7LjJZBJBQUGiqqqq2bm//vWv4oMPPmh2/PTp02LEiBEtjj9q1KgWc+0+/vhjsWDBgjbvJbNGK9LUtcJkMnXLvQhhzzGzY6McvlhBTKAnDpeZ/QkhOHz4MAMGDKBfv37WdWoywtGvYdB48BwAkTPAWA/ndrZ6SXBwMIDVthkjgs2rDGu+2cJ1gwaTMOMO67T2AH6Dw3F297DnmV0lFZUHkSQH+vSJ62kpLeLrMwmTSUd5+c+tttHs3g3Q68owtYYyLu6aN5odMWIEZ8+eJTMzE51Ox5o1a5g1a1azdqdPn6aiooJRo0Y1O3d53tn06dMpLCwkKyuLrKwsXFxcOHfuHAClpaWWSMFbb73FI488Aphz0hqNt1NTU0lNTWXKlCkAFBcXA1BfX8/bb7/N448/DkBlZaUlrPjZZ58xZswYPDw8mlxz8eJFvvvuO4u+xuMmk4nXX3/d0ldtbS01NTUAbN++HYVCwdChQ5tcU1FRwYcffsijjz56xXsxGAzkFBfjLpdx4sSJLruXzsSeY2anR9DqjaTlVfHo6NBm5zIzMykvL2fs2LHWd3whEapzYco/zI8HjASltzmcGXV7i5d4eHjQt29fMjMzufHGG9s9VHRAHxSYyMaLvz1xDzJb8MeRyQlVDefC0RRMJmOvDrv2Ziork/HwiEEuV/a0lBbp0ycBhcKTktL/0a/f1BbbqBMTcRgwAMfQ5q/B3ohSFUvVd9+hy8rCqRdWKOgMFAoFy5YtY+rUqRiNRh555BGioqJ4+eWXSUhIsEzSVq9ezbx585qFObOyssjJyWn3/86kpCT++te/IkkSY8aM4YMPPgBAr9czuiHv0MPDg6+++soSsvvnP//J5s2bMZlMPPHEE5Yct4yMDB544AHkcjlDhw5lxYoVlnFmz55NWVkZDg4OfPDBB3g1hM5Xr15tGfPOO+/k4YcfBsyTn6lTpyKTyQgICGDVqlWWvp555hmOHzfXTn355Zctyfut3UuVtp6HbpmCQpLw6tN199KptGdZrTd+2UOZtk1yZpkIWrhZ/C+tuU3FN998I9566y2h0+ms73jtA0IsChZCr/312IYnhXhzgBD6+lYv++GHH8Qbb7whDAZDu4c6fWCvGPnMp2LSPzZar7MHObV/j3h37nSRm9H6Nnw7raPXq8XOXYPFuXP/7GkpVyQt7c8iaXecMBqbv46MNTUiY1iMKHjjjR5Q1jG0Z86I9IghouK7DV3Sf28IZdrpfAq1OnGsqkbojKZuHdceyrRjczQay8YPbOr4r9FoyMjIQKVS4eDgYF2nNWVwagvE3A2KS3bKRc6A+irI2tvqpcHBweh0OgoKCto1VG11FTtWLCfMWUtWnQKt/soFzXsTQTFxyORyexWADlJVdQQhjHj2gsLlV8LXdzIGQ5Wlnuel1PzyC0Knw91GwpgAjoMGIXN3txc0t2MVaqMRZ7kMB1nvLsN0KfaJmZ0e4XB2BSE+rvR1a2o1cOzYMUwmU8cKlqeuBZO+uTVG6DhwcL3i7szGPLP2+pklrvyE+poa7pg2Fr1RcDyn0nq9PYSzqxsBQ6LseWYdpLIyGUmS06dPfE9LuSLe3qORyZxbrJ2pSUxE5ubWa93+W0KSyVDGxtonZnbajVEIao0m3Ht50fLLsS21dq4JhBBmY9nL/MtMJhOHDx8mKCjIYiBoRadm7zL/eOh/me+ZgxLCJsKprdCKJYabmxv9+vVr18TsbPJ+Tu3bzajZ85iQEAHQat3M3kpo/AhKc7KpLinuaSk2R0VlMu7uw1AoXHtayhWRy5V4e99MScn2JgnzwmRCnZSE6803I1lrRdPDKONU1J87h1Gt7mkpdmyAGqMJIcBdYVu5tPaJmZ1u52J5LWU1umaFyzMzM6moqOjYalneEShOb9VIlsiZoCmEvMOtdhEcHMzFixct9dJaok5dzY7PPqRf8CBG3DYHTxdHBvdzIyWr3HrNPUho/AjAXgXAWozGOqqrU3ulf1lL+PpOpr6+ALUmzXJMm5aOsaQU915atPxKKFUqEIK646k9LcWODaAxGJEkcLGvmNmxc2VaK1yekpKCUqm0bIu2iqNfgkIJ0bNbPj94MsgUcOqHVrsICQnBYDCQl5fXapvElZ+g1aiZ+sQzyBt29iQEmwuam0y2s43fyy8Az+v87HlmVlJVdRQh9HjayMTMp+8EQEZpya9FzTWNbv8NpXBsCWVsLEjSb6aguZ2rQ2004iqXIW/FpLe3Yp+Y2el2DmdX4O6kYHA/d8sxtVrNqVOnUKlU1jsp62rgxLdmOwznPi23UXpB8GjI2GwOe7ZAW3lm51IOkvFzEjfccTf9gn+1GEgI8qZaa+Bsse246UuSRGj89VxMS0Wv1fa0HJuhsjIZkOHp2fllWLoCR0dvPD0TmuSZqZMSUapUvd7tvyXkbm44hYfb88zstIneZEJrFLjZgI3R5dgnZna6ncPZFagGeiK/ZJfM0QbjyA6FMdM3mmtixrUSxmwkcgaUn4eS0y2eViqV+Pn5tWg0W6dRs+PTZfgGhXDDHXc1OZfQYDR7yAbDmUa9nuyTx3tais1gzi8bikLh3nbjXoKvz2Q0mlPU1V1EX1REfXoGbjYYxmxEqVJRd/w4wooSarbEtm3biIiIICwsjEWLFjU7/9xzz6FSqVCpVISHh+Pp+WtKyAsvvEBUVBSRkZH88Y9/tOQWjhs3joiICMt1jSapV+rrlltuwdPTkxkzZrSo8+mnn8bNzc3y+N///jdDhw4lJiaGiRMnkp2d3aO6NEbz8+M/77/XLbo6E/vEzE63otbqOVOkbpL435j0HxwcjI+Pj/WdHlkF3oMgqA1z2Ihp5u9XCGcGBweTk5ODXq9vcjzpi0+pU1dzy5PPIVc0tfEY6O2Cj5uTJURrKwRGRuGoVNrDme3EaKynuvooXr3cJuNyfH0nAVBSsgNNYhIA7uPG9Zygq0QZp8Kk0VDf4F5/LWE0GvnDH/7Ajz/+SHp6OqtXryY9Pb1Jm8WLF3Ps2DGOHTvG008/zZ133gnA/v372bdvH6mpqZw8eZJDhw6xu6G6A8DXX39tua6xokprfQEsWLCgibHrpaSkpFBZ2XQnelxcHCkpKaSmpjJnzhxeeOGFHtWlNhiRS3B9fHy36OpM7BMzO93K8ZwqTKJpftn58+epqqoiIaED4aHSc3BxP8TdB23lEXj4Q0CCOZzZCiEhIRiNRnJycn7VdziZ9D27uP72uU1CmI1IksSIYC9Ssm1rxUyucCA4Jp4LRw5d02VuOovq6uOYTDqbyS9rRKkciJvbEEpKt6NJTMQhMBDHsLCeltVhXOLMZbCuxYLmycnJhIWFERoaiqOjI/PmzWPjxo2ttr+0/JIkSWi1WnQ6HfX19ej1evr379/usS8v5TRx4kTc3ZuvDBuNRhYsWMA777zT5Pj48eNxcXEBYOTIkeTm5vaoLo3RhJtCzoQJE7pFV2diL8lkp1s5nF2BJIHqEmPZlJQUXF1dGTJkiPUdHl0FkhxU97SvfeQM2PEqVOVCn8BmpwcOHIgkSWRmZhIaGoq2RsOOT5fhMzCYkXfObbXb4UFe/HiykKJqLf09nK2/jx4idPj1nDm4j+LM8/QPtd036+6gsvIgIOHpOaKnpViNr89kss58gOsvLnjOvbtZKR9bwmHgQOReXtQdO4bX3a2/Jq+GM2f+gVqT0al9urtFEh7+f1dsk5eXx4ABAyyPAwMDOXjwYItts7OzyczMtJQRGjVqFOPHj8fPzw8hBE899RSRkZGW9g8//DByuZzZs2fz0ksvNXkOXN7XlVi2bBmzZs3Cz8+v1TYrVqzg1ltv7VFdepPAzbHp2lNP6OoI9hUzO93K4YsVRPR3x8PZHA6srq7mzJkzHUv6Nxrg+GoYPAXcr2vfNUMa8hJObWnxtLOzM/7+/pY8s6QvP6OmqpJbnni2WQjzUkYEewOQkmVb4cwQ1XCQJC4ctdtmtEVFZTJubhE4OLSywaQX4+s7GcdTAlGvw21cB2rQ9iIkSbIUNL/WaGnlurVJ9Jo1a5gzZw7yhuT2c+fOkZGRQW5uLnl5eezatYs9e/YA5rDciRMn2Lt3L3v37m0WCry8r9bIz89n3bp1PP300622+eqrr0hJSWHBggU9pqvxt3ipf1lP6Ooo9hUzO92GySQ4erGCGTH+lmNHjhzpeNL/2f+Bpqh177KW8BkMPhGQ8QPc8PsWm4SEhLB//37OHPqFtKQd3HDH3W2uJg3190DpIOdQVjnTY1r/JNnbcOnjid+gcC4cOcSo2V2zLH8tYDLpqKo6gr9/16zQdDVubkNxTXdDKA24jrC9Fb/LUapUaHbtwlBR0SW7S9ta2eoqAgMDm6RR5Obm4u/v32LbNWvWWAp1A2zYsIGRI0daEvJvvfVWfvnlF8aMGUNAQAAA7u7u3HPPPSQnJ/PAAw+02ldrHD16lHPnzhHWEAqvra0lLCyMcw35fjt27OCNN95g9+7dODk59ZiuutpaZsYNI7uHdXUU+4qZnW7jXIkGtdZgyS8zmUwcOXKE0NBQvL29re/w6Cpw7WdeMbOGyBmQvR9qW84JCwkJwWQy8eNXK+kbOJCRs+e12aWDXIZqgKfNbQAA8+7MwnNnqKm0Pe3dRbX6BCaT1uYS/y/F+aREfaQRk9x26rq2hkucCuCa8zMbMWIEZ8+eJTMzE51Ox5o1a5g1a1azdqdPn6aiooJRo0ZZjg0cOJDdu3djMBjQ6/Xs3r2byMhIDAYDpaWlAOj1ejZv3kx0dPQV+2qN6dOnU1hYSFZWFllZWbi4uFgmZUePHuX3v/89mzZtsiTL94SuzMxMnF1c2HcyA0mSelRXR2lzYiZJ0ueSJBVLknTykmP/lCTplCRJqZIkbZAkybPheLAkSXWSJB1r+ProkmuGS5J0QpKkc5IkLZUa1mclSfKWJGm7JElnG77bnrmOnXZxubHs2bNnqa6u7ljSv7oQzvwEqvkgt7LY+ZDpIIxwZluLpwcMGIAE1JjglieeRdHOYuoJwV6kF1RTU9965YDeSOhwczJ75tGUHlbSe6msMO9ctcX8MjC7/VOupS7aQHn53p6Wc9U4R0eDQnHNbQBQKBQsW7aMqVOnEhkZydy5c4mKiuLll19m06ZNlnarV69m3rx5TcKcc+bMYdCgQQwbNozY2FhiY2OZOXMm9fX1TJ06lZiYGFQqFQEBATz22GNX7Atg9OjR3HXXXezcuRM//wDWfvcDVXV6tHojphZCrgsWLECj0XDXXXehUqksE8qu1BUYGMhPP/3U5Hxtg02Gu0LWrbo6E6mt3ViSJI0BNMCXQojohmNTgF1CCIMkSW8DCCEWSpIUDGxubHdZP8nAM8AvwFZgqRDiR0mS3gHKhRCLJEn6C+AlhFjYlvCEhASRkmJ/I7El/rzuOLtOFXP4pUlIksR///tf8vPzee6556yP1f+82JzE/1SKOTxpDULAv4eCfxzM/2+z01nHDrPqv//Fxasvf/rri+3udveZEh78PJmvH72Bm8I6YPvRQwgh+OTJh/ALi2DWn9p/v78ljh57iPr6Qkbe0PJkvrdT8v4ySj/8kJJ3nfAJmcTQof/saUlXTeacu5AplQSt+rJT+svIyGiS/G0HjCbB6UI1JiGaTMYkJBwVMpwUMpwcZDgp5OafFTIUPVz+qKheT2G9nig3JQpZz21yaen5JEnSYSFEmysRbf4GhRB7gPLLjv1PCNG4LPAL0Hx7W1MxfoCHEOKAMM8EvwRubzh9G/BFw89fXHLczjVGY+FySZKoqqri7NmzxMXFWT8pEwKOfgUDR1k/KQOzrcaQ6XB+F+hqm5yqr63lf58sw00uodHp0Vrhih830BNJsj2jWXMVgBFkpR7FcJl/mx0wmQxUVR2xOZuMS9EkJaGMjaVvyARKSndhMtnWqm5LKOPiqDt5EmF/znYZZTX1GEwmQnxcifLvQ1g/NwZ4u+Dr7oSzgwyd0USpRkduRS3nSzSkF1STnl/N+RINuRW1lKjrqdbq0RmM3WbJozYaUcplPTopu1o6Y2r7CPDjJY9DJEk6KknSbkmSRjccCwByL2mT23AMoL8QogCg4Xs/WkGSpP8nSVKKJEkpJSUlnSDdTndRXqPjQmmNpXB5Y9J/fHy89Z1dPABl59p2+r8SkTPAUAfndzY5vOerz9GUlzFm+iyEEE1cotvCw9mBIdd52Gie2fXotXXkZpxsu/FvDLUmDaOxxmYKl1+OvqgYbVoabuPH4+szBYOhkqoq2482KFWxiLo6tKfP9LSUaxKjSVCqrsfd2QFXJwVymYSLowIvF0eu6+NMUF9Xwvu7E+3vQUR/d4L7uuLXxxkPZwUIqK7TU1BVR1ZpDacK1aTlV3OmSE12WQ2F1Voqa3XU6QwYO7HGsFEIao0m3GysaPnlXNWuTEmS/gYYgK8bDhUAA4UQQB3nDQAAIABJREFUZZIkDQe+lyQpCmhp6mr1X0MI8QnwCZhDmR1TbacnOHqxIb9soBdGo5EjR44QFhaGV0d2VB1ZBY7u5tqYHSXoJnD2NJvNRs4EIDv1GKk7tzFi1mxibhjFj0l7yMzMJCIiot3dJgR58d2RXAxGU48v6VvDwOgYFA6OXDiSTHBMXE/L6VVUVph9pDxtNPFfk5QEgNv4cTj0DUQmc6KkZDteXiN7VthVYjGaPXYMZXRUD6u59jCvlgn6uTtdsZ0kSTg5yHFykANN83ENRhP1BhP1BqP5u96EVm+kuk7fZALgKJfhqJDh7PBrSNTJQY5CJlmVy1VjNCFEU5sMW6TD7xySJD0IzADubQhPIoSoF0KUNfx8GDgPhGNeIbs03BkI5Df8XNQQ6mwMeRZ3VJOd3svh7AoUMomYQE/Onj2LWq3umEWGthrSv4foO8HRteOC5A4Qfot5A4BRj66ulp8+fg8v/0BuvOteHBwcGDBgQKsFzVsjIdiLGp2RU4XqjmvrARycnBk4LNZeBaAFKiqTcXEJwcnJt6eldAhNUhIO/v44DR6MXO6Ct9dNlJTusPm/s8LPD0X//tekn1lPc/lqWUdRyGW4OinwdnXCr4+SYB9XIq7zICqgD+H93QnyduE6D2dcnRQYhaC8RkdeZR0XSmvIaAiLnitWk1NeS3G1lqo6XaubD8BchkmSwNWGPhS3RIfUS5J0C7AQmCWEqL3kuK8kSfKGn0OBwcCFhhClWpKkkQ27MR8AGutMbAIebPj5wUuO27mGOJxdQZS/B0pHOSkpKbi7uxMeHm59Rye/BX0txD/Qdtu2iJwB2krI3seer1eiLivllieeQeHoCJhtM4qKiqitrb1yP5eQYDGata08MzDbZlQVFVKen9t2498IQhiprDxks/llJq2WmgMHcBs/3rLy4Os7Ga02F43mVA+ruzokSTIXNLdPzDqdMo15tax/G6tlHUUmSTg7yOnj4kg/D2cGeLswuJ87Uf4eRF7nQaiPK/6eSjxdHZFJEpp6A4XVWrLLajlTpCYtr5rThWqySmsoqKqjvEZHTb0BtcGIq1yGzIYrW0D77DJWAweACEmSciVJ+h2wDHAHtl9mizEGSJUk6TiwHnhcCNH4DvUE8BlwDvNKWmNe2iJgsiRJZ4HJDY/tXEPojSZSc6uIG+hFRUUF586d61jSP5i9y3wjIaADq22XM2giKJRc3LWW49u3Mnz67fiH/7qLJjg4GMBSBaA9BHgq8e/jTIoN5pmFxJk3C104Yq8C0Ihak4HRqLFZ/7KaAwcQWi1u48dbjvn4TAAkSkq395ywTkIZp0Kfn4++yB5o6SyMJkGJxrxa5nIVq2UdQZIkHBQy3Jwd8HFzIsBTSaivG5F+Hm1vPiitod4kqK3Vc774ks0HdXrqu3HzQWfQnl2Z84UQfkIIByFEoBBihRAiTAgxQAihavh6vKHtt0KIKCFErBAiXgjxwyX9pAghooUQg4QQT10S/iwTQkwUQgxu+G57Sw12rsipAjV1eiPDg7w4cuQIkiR1LOm/KB3yDpud/jvjE5GjC7qg8fy0+wJefgHcdPd9TU4HBATg4OBgdThzeLA3KVkVNvWPAMDDpx++A4O5cCS5p6X0Gn71L7PNFTNN0m5kLi64XP+r/5qjow99+gynpMT2J2aX5pldK2zbto2IiAjCwsJYtKj5OsVzzz2HSqVCpVIRHh6Op+evdYcXLlxIdHQ00dHRrF271nJcCMHf/vY3wsPDiYyMZOnSpU36PHToEHK5nPXr11OmqSftRCrzZkwkKiqKmJiYJn3t3LmT+Ph4VCoVN998s8VgduXKlfj6+lq0ffbZZwAkJiZajqlUKpydnfn+++8Bc33LsLAwJEmymLq2pksukziTfpJpE8cy8cbhzBw/iqNJW82bD65zJ+PYfuaNvpG7x9/E3TMncyL9NAVVdby3/FP8+vcnMjqGyOgY3l7yAYVVWn748X/ExMZeta6uwF6SyU6XczjbPNdWBXqwdvtRBg8e3OSfSbs5ugpkDhDTthN/e9mbfx3VumrmzbkFB8emy/ZyuZygoCDr88yCvPjheD55lXUEerl0mtbuIHT49SRvXI9Wo8G5oVTJb5mKyoMonQfi7Gw7ZbYaEUKgSUrC9aabkDWE5xvx9Z3MuXNvUVeXi1J5RbejXo1zZCSSoyN1x47hMdXKCiC9EKPRyB/+8Ae2b99OYGAgI0aMYNasWQwdOtTSZvHixZaf33//fY42hHK3bNnCkSNHOHbsGPX19YwdO5Zbb70VDw8PVq5cSU5ODqdOnUImk1FcXNxkzIULFzJ16lRMJhMlmnr6errz1apVDB48mPz8fIYPH87UqVPx9PTkiSeeYOPGjURGRvLhhx/y+uuvs3LlSgDuvvtuli1b1uSexo8fz7GGiXN5eTlhYWFMmWL+W910003MmDGDcePGtfi7aNTViIuLC19++WWLuv767B9ZsnotM4fHsXz5ctZ++h6frficA+5O3DnnLv7xzr+p15s3IpSotQQNu56vtuwGoKa6kuk3x3dYV2dj2xlydmyCwxcr8evjjLroIhqNpmNJ/4Z6OL4GhkwD176doisnLZVjR84S711AgDa1xTbBwcGUlpaiVrc/mT8h2LzT1DZtM0YgTCayjh/uaSk9jhAmKitT8PSyzdWy+owMDEVFTcKYjfj6TAKw+XCm5OiIc3T0NZNnlpycTFhYGKGhoTg6OjJv3jw2bmw97Xr16tXMn2+ucZuens7YsWNRKBS4uroSGxvLtm1mQ+Tly5fz8ssvI5OZ3/IvLU30/vvvM3v2bPr164daa7avGBUXzeDBZo9If39/+vXrR6NFlSRJVFdXA1BVVdVqLc+WWL9+PbfeeisuLuYPrHFxcZaUkcu5VFcj4eHhLeoSQiCQMNbUWHwy/f39UcjNuzudHeRX3Hyw+6fNTJ16S4d1dTb2FTM7XU6jsWxKSgoeHh6WF5ZVnN4KdeUQ1wlJ/4Beq+Wnj5fi2d+Pm2OBU1tg0ivN2oWEhADmPLNhw4a1q+8h13ng5qTgUFY5t6kC2r6gF3FdWDhKdw8uHDnEkJvG9rScHkVTcwaDodJm/cvUiYkgSbiNHdPsnItLMK6u4ZSUbGfggId7QF3noVSpqFi1CpNO12xlsKP839lcTmrqOqWvRqLdlPxj8JVXJ/Py8hgwYIDlcWBgIAcPHmyxbXZ2NpmZmUyYMAGA2NhYXnvtNZ5//nlqa2tJTEy0rLSdP3+etWvXsmHDBnx9fVm6dCmDBw8mLy+PDRs2sGvXLpKTk6nWGvBwdsDF8depQXJyMjqdjkGDBgHw2WefMW3aNJRKJR4eHvzyyy+Wtt9++y179uwhPDycxYsXN7kXMBf/fv7559v8XV2q69ChlnNeL9VVbxK8/P4H/O7O23m6nbqcGyZsAP/74btO09UZ2FfM7HQphVVa8irrGOLrxIULF4iPj7d8arOKI6vAIxAGNf/03xH2rvmCquIipj7xDA7RM6H0NJSebdbOz88PJycnq8KZcplE3EBPUrJsb8VMJpMTEpdA5rHDmEy2X+z6arB5/7LEJJQxMSj6trzC7OsziaqqFPR623ueXooyToXQ69GmpfW0lKumpbzU1ny81qxZw5w5cyybqKZMmcK0adO48cYbmT9/PqNGjUKhME+w6uvrcXZ2JiUlhccee4xHHnkEgGeffZa3334buVxOvcGESQj6efya0lFQUMD999/Pf/7zH8v/7cWLF7N161Zyc3N5+OGHLROamTNnkpWVRWpqKpMmTeLBBx+8VC4FBQWcOHGiXSHAS3W1xOW61EYjX32wjI2bN/eork5DCGGTX8OHDxd2ej9bUvNF0MLN4uN128Srr74qqqqqrO+k4qIQr/QRYufrnaIpJ+2EeHfudLHzPx+ZD1TmCPGKhxB7/tVi+6+//lq89957Vo2xZPsZEfyXzaKyVne1crudU/v3infnThe5GWk9LaVHOZ76pPj555t7WkaH0BUVifSIIaJk+UettqmqOi527AwV+fnfdqOyzkdfXCzSI4aI0hWfX1U/6enpnaSo4+zfv19MmTLF8vjNN98Ub775ZottVSqV2LdvX6t9zZ8/X2zZskUIIURERITIzMwUQghhMpmEh4eHEEKI4OBgERQUJIKCgoTSxVX09fERGzZsEEIIUVVVJeLi4sQ333xj6bO4uFiEhoZaHmdnZ4vIyMhmYxsMBssYjSxZskQ89thjLWoNCgoSJSUllseX6nJ1dRW+vr5X1HUoK0cMCAnpUV2X09LzCUgR7Zjf2FfM7HQph7MrcFLIKL+QSnh4OB4eHtZ3cuy/gIC4e69aj75ey08fvUef/tcxel7DJ6c+geCnMoczWyAkJITy8nKqqqraPc6IYC9zSc+LtrcaERwbh0wu/03vzhRCUFmZbLP5ZZrd5qRmt/HjWm3j7j4MJ6frbD7PTOHri0Ng4DWxM3PEiBGcPXuWzMxMdDoda9asYdasWc3anT59moqKCkaNGmU5ZjQaKSsrAyA1NZXU1FRLMvvtt9/Orl27ANi9e7fFQzIzM5OsrCwOpp5i8rRZvPf+Mm6//XZ0Oh133HEHDzzwAHfddZdlDC8vL6qqqjhzxlwGa/v27ZZC3QUFBZZ2mzZtalbA+9J8uLZo1JWVlcWcOXP48MMPW9UlhEDu4YGmurrHdHU29hwzO13K4ewKwrwd0FbXkJCQYH0HJhMc+wpCxoJX8FXr2bd2FZVFBcx9+U0cnJ1/PRE5A3a9DtX54NE0mbUxzywzMxOVStWucVQDPZHLJFKyKhgX0XVJol2Bk4srAUOiuHDkEKPveahHtRjK6pB7OiF1s5N3Te059Ppym/Uv0yQmofD3w+kKJs6SJOHrM5n8gnUYjXXI5cpuVNi5KOPiqPnlAEIIq0r49DYUCgXLli1j6tSpGI1GHnnkEaKionj55ZdJSEiwTNJWr17NvHnzmtyrXq9n9GhzeWoPDw+++uorSyjzL3/5C/feey+LFy/Gzc3NYmUBYDSZKNXU4yCX4dRQyuibb75hz549lJWVWXZcrly5EpVKxaeffsrs2bORyWR4eXnx+eefA7B06VI2bdqEQqHA29vbch2Yc3RzcnIYO7Zp3urSpUt55513KCwsJCYmhmnTpjXRdjkt6Vr+2QpcwiNZuvyjHtPV6bRnWa03ftlDmb2fOp1BhL24Rdzzzjfi3//+tzAajdZ3cm6XOcyYuu6q9eRmpIl3754hdqz4sPnJogzzOAc/aXbKaDSKRYsWtbpk3Roz398r7v54f0fl9iiHfvhOvDt3uqgsKuwxDfW5apHzlz2ieMUJYaw3dOvYOTlfiR07Q0VNTWa3jtsZGOvqRIYqThS89vc225aV/Sx27AwVxcXbu0RL5vESsWLBXqEu13ZJ/42UffWVSI8YIupzcjvcR28IZfYEhVV14nhOhaip1/e0lA5RoNWJY1U1Qm809bSUJthDmXZ6JSfzqtAbBU7VeQwfPrxjSf9HV5mLjQ+ZcVVa9Lp6fvpoCR4+/VpeBfKNAO9BLYYzZTIZwcHBZGZmWmUaOzzIi2M5leiNpqtQ3jOExptDeBeO9lwVAPWeXJDLqD9bQel/TmLSGrpt7IrKgzg59kepDOq2MTuL2oMHEXV1VwxjNuLpeT0KhXuXhTOP/C+bumodJ3Z3bZmva9FotjtoXC27fCemLaExGFHKZShktrtSejn2iZmdLqPRx6u/opa4hn+cVlFbDhmbIWYuODi33f4K7Fv7FRUF+Ux9/I84OrcQspEkczgzay/UNc8LCwkJoaqqioqK9ueMjQj2Rqs3kZZffTXSewRv/wC8/Px7rDyToUJL3YkS3Eb54T0vAl22mpLPTmCq1Xf52OKS/DJbDIupExORXFxwub7t/DiZzAGfvhMoLd2FEJ27C7csX0PBuSoUTnLS9uah13XdLl+n8HAkF5drxs+suyjV6DCaBP09uqYmZldjFIJakwk3Gy9afjnX1t3Y6VWkZJXTR1aPasgg3N3dre/gxDow1kPc/VelI/9MBke2bCR28q0MjI5tveGQmWAywJn/NTt1qZ9Ze0kIMhvN2mJBczCbzeacPI5O27l+Tu1B83MeIOF2UwAusf3oe18k+sIaSj5JxajWdenYdXVZ6HQlNlmGSQiBJmk3rjeOQubUvjdbH99J6PXlVFYd6VQtaXvykSkkJj0USX2NgTMHCzu1/0uRFAqUw4bZJ2ZWYLhktUxpo6tlNUYTQoC7oovtK7oZ+8TMTpcghOBQZik+qDvm9C+E2bvMLxb8YjqsQ6+rZ9vy93Dr25cx97ZhpBkwHNyug1Obm53y8fHBzc3NKj+zfh7ODPR2sUk/MzCHM40GAxdPHO/WcU21emoOFeIS64vC0zy5UA7ti89DURjKtJR8nIqhsr7Lxq+oNO9GtcXE//pTpzAUFuLegtt/a/T1HoMkOVLaibUz9fVGTv9SQFh8P0JVvvgOdOf4zpwurR+rjFOhPX0aU21tl41xLVFm46tlAGqDEUkCV/uKmR07bZNTXkel1kSQm4nQ0FDrOyg4BkUnrnq17MC6/1KRn8vU3z+Do7KNupUymbnk07kdoG+6SiRJUofyzBKCvEjJLre5guYAAUOG4qh06fY8M83BQoTOhNvoplUTnMO88Hl0GEaNjpKPjmMo7ZqVvMqKZBwdfXBx6cDztodRJyYC4Da2/VUbFAo3vL1vpKRke6c9T88eKkKnNRI1JgBJkoidEEhFYS05GV23euwSFwdGI3UnTnbZGNcK18JqGYDGaMRVLkNmgykHV8I+MbPTJSSezAZgYmxIx53+Fc4w7K6227ZCwdnTpPywgWETpxIU0z6bC4bMAH0tnE9sdiokJASNRkNpaWm7NSQEe1Oq0ZFdZnuf4uUKB4Jj47lw5FC3TSyFwYRmfx5Ogz1x9G9eRN0pyAPfx2IQOiPFHx9HX1TTueMLQUXlQTw9bTO/TJO0G+eYGBQ+PlZd5+szmTrtRWpqznSKjpN78vD2d8VvUB8Awob3x8XDkeM7u24TgDLWnKZg3wDQNtfCapneZEJrFLh1tQt/D2CfmNnpEnYez8QBIzNGdyCMqa+DE+shchYoPa2+vKaygn3ffM13i17FzbsvY+/7XfsvDh4NTn1a3J3ZWNTWqjyzhoLmh2w4z6ymopzizPPdMl7t0WJMaj3uY1qvKegY4Ibv72MAiZKPU9Hltr/AfFtotbnU1xfYZH6ZoaQEbWoq7u3YjXk5Pj4TAYmSkub5ldZSlFVNyUU10Q2rZQByBxnRYwO4mFZGRWHnTqYbkXt64hgaavN5Ztu2bSMiIoKwsDAWLVrU7PzFixcZP348cXFxxMTEsHXrVsu5t956i7CwMCIiIvjpp58AsxmtSqWyfHl4eLB48WI8nB3YvHEDUVFRyGQyUlJSWhzLzc2Nd999F4CcnBzGjx9PZGQkUVFRvPfee5a2x44dY+TIkahUKhISEkhONqcEJCUl0adPH8v4f//731vVtWTJEgDWrVvXpi4vDw++WLoEd4Ws23QtWLCAIUOGEBMTwx133EFlZWV7/6zW0R5Pjd74Zfcxuzq0Z8+Ks5OniKIlS4Sxrq5T+9bpdCL+r+vEpNc3dqyDY2vMnmIXdlt1WXF2pvjxw8Vi8T23iXfvniE2vPN3UZydaf34638nxKJgIQxNfX1MJpP417/+JdauXdvuroxGkxj2yjaxcP1x63X0AmqqKsW7d88Q+9f9t8vHMhlNouBfh0ThksPCZGrbk0hfWivy3zoocl/eJ7SZlZ2iIS9/ndixM1So1ac6pb/upGLdOpEeMUTUZWR06PpDKXPEweSZV61j5xfp4qM/Jon62qavn5qqerH8D4ki6euu+93m/fVFcfqGke16/lxOb/AxMxgMIjQ0VJw/f17U19eLmJgYkZbWtDTaY489Jj780OzFmJaWJoKCgiw/x8TECK1WKy5cuCBCQ0OFwWBo1r9vv/7ixwPHRW29XqSnp4tTp06JsWPHikOHDjXTc+edd4o5c+aIf/7zn0IIIfLz88Xhw4eFEEJUV1eLwYMHW/RNnjxZbN26VQghxJYtW8TYsWOFEEIkJiaK6dOnt3nf/fv3F1lZWUII0S5d0+64U/zp9TeEyWTqNl0//fST0OvNz+sXXnhBvPDCC61ea/cxs2MVQggK//E6hoICypZ/xIWZs9Ds/bnT+k85fpJykzOjBvfvWAdHV5ld/oNubrOpMJnIPJrCutdf4ssFT3H6wF6iJ0zl4X9/xPRnn8E7oAOu+0NmQF05XDzQ5LAkSYSEhJCVlYXJ1D5vMplMIiHYm5Rs29wA4OLRB7+w8G4pz6Q9XY6huA73MYHtCiMq+irxfTwWubsjpStOoj179b/jyopkHBy8cHUdfNV9dTfqpCQUfn44RUR06Hpfn8mo1Wlotfkd1qCt0XP2UBHhI/rjqGyau+Ti4Uj49f059UsB2pqusT1RxqkwVlais2JVuzeRnJxMWFgYoaGhODo6Mm/ePDZu3NikjSRJVFebLXiqqqrw9zdXKtm4cSPz5s3DycmJkJAQwsLCLKtDjfxv+3YCBgYTOXgQSkcFkZGRRLTyfPn+++8JDQ0lKirKcszPz4/4+HgA3N3diYyMJC8v74q62sPOnTsZNGgQQUFm38C2dIWEhBA8ZAiOMhmSJHWbrilTpliqKYwcOZLc3K4Jzdtu1p+dDqPeto3agwe57pWXcQwJofDV18h57DE8pt1Kv4V/waH/1ZUQ2nLgJAJvJsSGWH9x+QWzl9iEl8zJ+K2g19WTsSeRw1s3Up6Xg5uXNzfPf5CYSbegdHOnsjKF/Qdm4NkngdjYT63TEDYJ5E7mcGbI6CangoODOX78OCUlJfTv376J5/AgL3adKqaiRoeXq6N1WnoBofHXs2/tKmoqK3D19OqycdR78pD3cUIZ0/78KIWnE76/j6F0xUlKV6bR955IlFF9O6yhojIZT88RSJJtfWY11ddTs28/fW6/rcO5cb6+kzl3/m1KSncwIPCBDvVx+mAhBr2J6DEBLZ6PmTCAjP0FpP+cT/zUzjfvtRjNHj2GU0gH/v808NoPaaR3sv/gUH8PXpkZdcU2eXl5DBgwwPI4MDCQgwcPNmnz6quvMmXKFN5//31qamrYsWOH5dqRI0c2ubZxctLIl1+v5pbb7qSf+5Vzy2pqanj77bfZvn27JYx5OVlZWRw9epQbbjDvXl6yZAlTp07lz3/+MyaTif3791vaHjhwgNjYWPz9/Xn33XebTPYA1qxZ0656lY26ftj2Ey8tehunFl6n3aXr888/5+67725Tc0ewrf8+dq4aU20tRW+/g1NkJJ5z5+I6ciQhmzbi88enUe/YyYXp0yn/6muEsWNmkMXFxaQV1SIBcQM78CZ+9CuQZKBquWC5OX/sKz598mG2f7oMhaMj0576E48uW8ENt9+F0s2dkpIdHD32ACaTltKyXdTUXLBOg5MbDBpvts24LOn90rqZ7WVEsDfwq+GurREaPwLo2ioAuhw1uswq3G72t7ouptzdEd//NwwHfzfKvk6n9lhxhzRotflotTk2mV/W6PZvjU3G5bi4hODiEkZJB20zhBCk7cmjX7AHvgNb9i30CXQjIMKLE0m5GLugIoZjaCgyDw+b3QAgWthkc/lEe/Xq1Tz00EPk5uaydetW7r//fkwmU5vX1tZp2bZlM7Nnz2lzJ+Yrr7zCc889h5tb8w04ABqNhtmzZ7NkyRI8PDwAWL58OYsXLyYnJ4fFixfzu9+Zc3vj4+PJzs7m+PHjPP30082Kfut0OjZt2tSkWHpbuoTSbBLuJG/6u+kuXW+88QYKhYJ77235fepqsa+Y/cYo/eQTDIWFBPz7X0gNu1lkjo74PvkkfaZPp/C1v1P0+utUbdjAda+9hjL6yp/wLiclJYUS4c4gXxf6KB2sE2c0wLH/mlesLiskXpKdyeEtGzm1Lwmj0cig4TcwfPptBEZGN/nnk5+/joxTL+LhMYzIyLdJTp5Fbt6XRIS/ap2WITPgzDYoTDV7qTXg6emJl5cXmZmZTT6dXomYwD44yCUOZZczaWgHw7s9iG9QCG59fbhw+BDDxk/pkjHUe3KRnOW4Xn9dh66XuTjg+2g0pSvTKV97GqEzWd2XLfuXaZKSkJRKXG64Ou2+vpO5ePET9PoqHBz6WHVt/tlKKgprmfBA5BXbxU4cwNYPU7lwtITBCZ37epBkMpSxsVe9AaCtla2uIjAwkJycHMvj3NzcZqG3FStWsG3bNgBGjRqFVqultLS0zWu/2fADQ6JjiRrU9krlwYMHWb9+PS+88AKVlZXIZDKcnZ156qmn0Ov1zJ49m3vvvZc777zTcs0XX3xhSbq/6667ePTRRwEsEySAadOm8eSTT1JaWopPw87hH3/8kfj4+HZFIBp1GRYsoLqqCoVMhptS2a26vvjiCzZv3szOnTu7bOe2fcXsN4QuO5vyFZ/jMWsmLg3x+EtxDApiwIrP8P/Xu+iLi8iaO5fC19/AqG7frjedTsexY8cpw4MRIR0IJ53fCeoCi3eZMJm4cPQQ6/7xN7584WlO/7KXYROn8sjij7h9wUsMGDrM8sIQQpCV9REZp/6Ct/dNxKlW4eY6mP79p1NQ8B0Gg5U79yJuNa/cZTQ3mw0JCSE7O7vdeWbODnKGBfThsI0azUqSxKD4EWSnHsWg7/zcIENZHXUnS3G7wQ+ZU8c/K8qcFPg8HIVzuBcV351F/XNe2xddQmXFQRQKD9zcOpaj1VMIIVAnJuF6443tdvtvDV/fyQhhpLSsuV1MW5zck4eTi4KwhCunQgRH98XDV0nqrpwrtusoSlUs9efOtfv/Vm9ixIgRnD17lszMTHQ6HWvWrGHWrFlN2gwcOJCdO3cCkJGRgVarxdfXl1mzZrFmzRrq6+vJzMzk7NmzXN9QlstgNLF27RruvGtQl5/YAAAgAElEQVQuSse27SX27t1LVlYWWVlZPPvss7z44os89dRTCCH43e9+R2RkJM8//3yTa/z9/dm9ezcAu3btYvBgc55mYWGhZTUvOTkZk8lE376/vj+sXr26XWHMRl2ZmZn8eDKDR596utt1bdu2jbfffptNmzbh4tKGL+ZVYJ+Y/YYoemsRkoMD/f7851bbSJJEn+nTGbRlC17z5lHx9ddcmDad6h9/bNPLKi0tjWKtRJ1RIr4jYcwjX4KLD/qg8Rzf/iMr//QkGxa9Rnl+LqPveYj/9+FKJj7yBF5+TfNXhDBx9twbnL/wT/r3n0VszCcoFK4ADAh8EKOxhvyC9dZpcfWBgaNarAIQHByMVqulsLD9JWYSgr1Jza1Cq++6eoFdSWj89ejrteRmdL55p/rnPJBJuN3U/qTc1pA5yul7/1CU0X2p2nyB6p0X2+3B9mt+mW35ItWfPo2hoKBDNhmX4+E+DCfH/laHM2urdVw4WsKQkX44tPHGL8nMhrOFF6opzKy6Grkt4hIXB0JQdzy10/vuahQKBcuWLWPq1KlERkYyd+5coqKiePnll9m0aRMA//rXv/j000+JjY1l/vz5rFy5EkmSiIqKYu7cuQwdOpRbbrmFDz74AHlDVORicSUH9iRy/7y5TcbbsGEDgYGBHDhwgOnTpzN16tQr6tu3bx+rVq1i165dFjuJRruOTz/9lD/96U/Exsby4osv8sknnwCwfv16oqOjiY2N5Y9//CNr1qyxfKCura1l+/btTVa42tJVazRhEuB4yWpVd+l66qmnUKvVTJ48GZVKxeOPP97Wn7RjtGfrZm/8sttlWEd1YqJIjxgiSj9bYdV1tamp4vwdd4j0iCEi+3ePivrs7Fbbfvrpp+KxRf8RQQs3i/PFausEqouE5qX+4uc3HhbLfjdfvDt3uvhy4R9F+t5EYdDrW73MaKwXJ04+K3bsDBWnz/xDmEzGZm0OpcwR+/aPa/HcFdn/gdm2o/Rck8PV1dXilVdeET///HO7u/rpZIEIWrhZHMoss05DL0FXrxVL7rtT7PzPR53ar0GjE7kv/SzKvjndqf2aDCZRtvaUyFm4R1RsvdCmfYJWWyR27AwVWdmfdqqOtjCaTB2ydriUkuXLRXrEEKErKuoUTRmn/k8kJkULg6H9NjopP2aKZb/fKcoLNO1qX1+nF588kyR++uxkR2W2ikGtFumRQ0Xx0vetuq432GV0BXqDUZzMrRRZpe372/R2CrQ6cayqRuiNV/e66Wrsdhl2rohJp6PorbdwDAnB+/77rLpWOWwYId98Q/8XX6Tu6FEuzJxF6fLlmHRNC0kXFhaSm5tLvXsAXi4OhPi4tnuM4qwLbHv3JT45E88vqSUEDhnK3a8s4r63lhB58zjkipbDWwZDDcdT/x9FRZsYFLqAwWF/a3E33YDAB6mru0hZ2W6r7p0h083fLzObdXd3x8fHxyqj2eFBjUazthnOdHB0YmB0DBcOJ7d7Bao91PxSgNCbcG9lF19HkeQSXnPCcR3ph2Z3LpUbzyNMreuuqDTvfPPqxsR/IQT3pl5gcsoZcrUdL8yuTkzEedgwHPpd3W7qRnx9JmE01lJRsb/txoDJJEjbm09AhCde17Xvde/orCDyZn/OHy5GU6G9GrnNkLu54TR4sM0bzXYWpRodRiHo5+7c01I6BY3BiFIuQyGzvcoc7cU+MfsNUP6fleizL9L/b39DcrTerkFSKPB+4H5Ct27Bbfx4St5bSubtd1Bz8FePnMOHDyOXy7lYoyB+oFebSZHCZOLCkUOs+8eLrFr4R06fziNmgOCRJR9z259fInBo9BX70OnKOXrsfsrL9xE55C2Cgx9vtb2v71ScHPuTk/uFdTfuFQTXDWs1nJmdnY2xnbtX+7o5EerryuHszqsAIIToMj+olgiNH0FVcRHleZ3j3SP0JjT783GO8MKhf/sn8u1Fkkl43jYIt7GB1PxSQMX6Mwhjy5Ozyspk5HI33NyGdrqO1vimsILEcjWna7RMP3yGE2rry3YZSkvRpp7ArRPCmI14eY1ELndrdzjzYloZ6jItUaOtm1zHjAtECMGJ3dblArYHZZyKutTUDu8uv1YwGE2Uaerpo3RoV25Zb8coBDUmE+7XWNHyy7m2784O+oICSj/6CPfJk3C7+aar6suhf38ClyxmwCcfI3Q6Lj74IPkL/0JtYSGpqakEh0eRWVZLfFDr+WX6ei3Ht2/lP396kg1vv0Z5fh6jp03k92G/MPGee/C6ru08o7q6PA4fuRuN5hQxw5bj7z/3iu1lMgcCAu6hvHwvNTVWlhYaMhNykkFd1ORwSEgIOp2O/Pz2m3GaC5pXYLrCyk17EUKw64sMvvjrPqpKuqaY9+WExDXYZnSS2WzNkSJMNXrcrlB+6WqRJIk+twTjMSWI2iPFlK/OQBiab9qoqEjG03M4Mln3bFSv0Bt47XweCR4u/JQQjkKSuO3oOXaUWeedpdm9B4TAfdy4TtMmkzni03ccJaU7EaLtiU3a3nyUHo6EqnytGsfDR0mIype0vXnodZ07gXKJi8Ok0VB/rntKifVWLKtlHtfGalmNwQj/n73zDo+q2tr470wmk94bIQlpBEghpFFUkHZBOlbEAl4FRewdbIgXxAo2RAH1glxBQJQiRTqRFkijJEB67z0zSSZT9vdHQiCmTUKi3vv5Pk+eTPbZZ501JzPnrLP2Wu8rwFL+3x9ktoe/A7M2cPRKEcv2XPqz3bhhFH34Iej1OC9Y2G02LW+9FZ9dO3F4fB6Ve/Zw9MknUavVGPdq6HYJbyUwU5aXcfyHDax54mEOfr0Khakpk555mbmff8MQ2xRMzUwh8I4Oj61UJhETO4P6+mJCQtbj5PQPg3x2c5uJJCnIydnQuTc7YDIg4MqeZsNXdTM7w2cW4WVPRY2GtBJl53xoBQm/5XH5dAHaej1ndnWSp62LsHZ0wsnTm7TYG+czE3qB8rdcjN0sMfHpHC1DZyFJEtZj+mAzxYfai6WUfJeI/rpAoL6+hJqaFGz/QJqMd9PyqdTq+KC/BwGWZuwO70dfMxNmn09jfW6JwXaUR48gd3HBxL99iorOwslpHBpNKZWV7S8HVpfVkXmhhICbXTGSd/52MmiMB2qVlqQowxtpDIFZSAjw/1vQvFm2zPh/I5Cp1umRJLD4O2P2/xPx2RWsiUzjt+TiP9uVLkMVdYaqPXtxePRRFO7dW8MjMzPD+bnn8Nn+M2l+flhXVnJh026MJBjkfk14vCgjjb1frGDtk48QtX0L7v6B3Lv4PR5Y9jH+t4zESFcLF39uCMpMWiczvIqKyhhiYmcihJ7wsM3Y2Q422F+FwpFeLlPIL9jWOeoMl8AGeajfLWdaWFjg7OzcOUHzbqozK0yv4rctSfQJdCB0XB+SzhZSnP3HUAP4hA0h90oitcobO17dpVK0JYbLL3UHrIa7YXenH+rkckr+nYBerQWgvKIh0Pyj6stiK1VsyCtlrpsTAZYNRJm9TIz5ObQvo+2tWZCUw79S8tB3UMunr69HeeIklqNGdfs5dHAYiSQZU1zS/nJm4vE8BBAwomsdta59bXDqY8W5Q9ndWrto3KcPRvb2/6/rzEqUanRC4PI/ki0DqNbpsDCSIfuDrhl/Fv4mmG0Dj4/0ZXtcLot2JLD32RGY/pc9cQitlsKlSzF2c8Nh7pwW2wtUBSyLWkadtg5LhSXmcnMsjC3a/LE0tsTc2LzptZncDEmSKDM3p8TUlJE+vnwSW49PeQ6VHy8nd/gwYg/tIzvhPMYmpgwaN5GwidOw7eXa3JGLP4FGBWHtS8CUlBzhwsWnMDHpRWjIeszMOr/85e4+m/yCn8jL/5E+Hg8btpMkNZDNRq2GuiowvUZK6O3tTUxMDFqttkk/rT14O1rgYKEgOqOc+4b06bT/ALXKevatuYCFtQnjHmmoh0o8kcfp7alMfTqkSzY7A5+wwUT9vJmMc7H43zKyy3aqI3MxsjPBLMhw+aXugMWQXkgKGWVbrlD89UWcHg6koiIKmcwMK6ugHj++Vi9YkJSDi8KYl72bE+BayI1YP9Cb15JzWJVdRHZdPZ/598GsjexATdQZRE1Nt9aXXYVcboW93U0UF++nr+/CVgM/nU5P4vE8PIMcsHYw69JxJKmBOuPguktkXyqjT0DX5bR+b9csJOT/bWCm1ekpUdZjY2b8X3fvagsavR61TmB/A1yH/y34O2PWBkyNjfjX9CDSS1SsPvbHLBV1J8o3bkKdnIzzwgXITJs/MWn1WhZELuB0/mlUWhXplemcKTjDrrRdfHvxWz6J/YR3ot7hteOv8eyRZ5m7fy4zd89k2vZpjN06lqEbhzLou0EM2ziMxVsWo5f0rHU6xkV7d+zkJWw/eZAdn31AbkoiJmMCsHtuMtUjehGtTuBk3knOF58ntSKVAlUB1XHr0Tn2A/e2s1/5+ds4f2EeFhZ+RIRv6VJQBmBtPRAbm3Bysr8zqHamCQOmgF4DyfubDXt7e6PVag0WspUkiXBPO6K72ACg1wsOfJtITXU9E+YFYWphjKmFMWETPMlKKCP3Ss93fPbq64eZtQ3pN7Ccqc6soj6zCsvhbkhGf/yTr3mIMw4PBqDJU1K85gLlpVHY2oQhk3VSqaILWJdXwgVlLf/yc2u1TkYuk3i/nzuLfHuzq7iCGfGplNZrW7WlPHIEydQUCwMVKDoLR6dx1NZmoVIlt7o9Pb6Emqp6gjpZ9P979A13wdxawblD3SsIbRYaQn1mJtry/65O6H379tG/f3/69u3Le++912J7VlYWo0ePJjQ0lODg4Ca+rtLSUkaPHo2lpSWPzX8CfWO2rLq6uonbKyQkBEdHR5577rl2bWVkZGBmZta0z1W+rvZsRUZGEhYWhlwu58cfW/JGVlVV4ebmxlNPPQU0cIVNnjyZAQMGEBgYyMKF18ptWvOrWqcnNzMTT1vrv5RfPQGDQk9Jkr4FpgBFQoigxjF7YDPgBWQAM4QQ5VLDo9WnwCSgBvinECK2cZ+HgDcazS4VQqxvHA8H1gFmwB7gWdGdee0uoKIyBk/TOCYPDOWLoylMD+mNVycoIP5MaEtLKf78cyxuuQWrf7SswVoVv4rYoljeG/Eek30mN9smhECtU6PUKKnR1KDSqJpeKzVKVBpV02tlrZLa1Fq0DvXYJNig08uxqymm1MGIfjnFBGRVEVOexLfqPZTYtHEDNm74Mds4tCk7Zy43x1JhiYXcggCjbPrpL1Bt5E6y8RiSUvY2zDE2x9LYstXXxu3cYD3cH+JiwjOUlh7D0XGMYSfUYwhYODUsZw68u2nY07NB2iQjI6Op5qwjRHjZsT+xkOJqNU4dCAn/Hmd3p5OdWMaoB/rj7Hktcxc8yp0LR3I4+XMqdy8I79GlQZnMCJ/QCFJjzqDX6ZAZdf5pvDoyB8lMjkVE1+SXugNmAQ44/jOQoo1RqGqTcLKd0OPHLFRreC8tn9H2Vkx1aruuTpIknujjjLupgqcvZTIlNonvg33xMb/2eRFCoDx6FIubbmrx4NVdcHIcy5Urb1JccgBLy34ttif8loulvQl9gm4sy2VkLCNopBtndqVTXqAymHKjI1wvaG41pusaon8kdDodTz75JAcOHMDd3Z3Bgwczbdo0AgKudQsvXbqUGTNmMH/+fBITE5k0aRIZGRmYmpqyZMkSzp0/z/Ez8U3ZMlNjK+Kvq7ULDw9vIk5tyxaAr69vs/2ggSqoLVt9+vRh3bp1bYqev/nmm4wc2TzL/tJLLzF69Gjq6+sZO3Yse/fuZeLEia36FXnpCkbSX8+vzpSzGApDc4LrgJXAd9eNLQQOCSHekyRpYePfC4CJgF/jz1DgS2BoYyD3FhABCCBGkqSdQojyxjmPAadpCMwmAHtv7K3dGIoK95Cds47pnrdw9Mp9LNqZwPqHB/9h9TA3gqIVK9DX1uLy+mst/D2Ze5KvL3zNXX53tQjKoOGmYCo3xVRu2hAmt4PD+/YSqYvCNjaTbKM+4ACPPvEw4eHBoNVS9t13DFm5kiHfgvFjD6K5ewI14lrQp4z/D6qMSGpueQalJJoFfSqNEi9tNP2kIi7WmbGxTElNxlqD3r9Cpmhang13CWfeoHl4WHkA4OQ0HhOTXmRnrzc8MJMZQf9JcHEbaNUgb7hBmpmZ4erqSnp6OqMM7IqLaBI0L2NCkGsHs68h40IJ0bszGHCzKwHDm9fzyBVGDJ7izZENl0mLK8Y3rHv4rNqCT9hgEo4dIi/5Mu4DOqcpqCmppS6xFKtRHshM/twlFlM/O+R310EhiEN2aJ1rkXdxSc4QvJWSi0YIlvkZVlc3zdkWVxNjHrqQxpTYJNYFeTPEtqEOU52UjCYvD4fH5/WYvyYmLlhbh1BSfBBvryebbasorCHncjlDp/kg6wY+qcARbsTszeT84RxG3t89klimQUEgl1Mb/98TmJ05c4a+ffvi4+MDwMyZM9mxY0ezwEySJKqqGrp3Kysrm/QwLSwsGD58ONHnExG0XluWnJxMUVERI0aMaNeWIfi9rasPpzJZy4W4mJgYCgsLmTBhAtHR0QCYm5szenTD/0WhUBAWFta0+tCaX9U6PRYGNJj80X71BAwKzIQQkZIkef1ueDowqvH1euAoDYHZdOC7xozXaUmSbCVJcm2ce0AIUQYgSdIBYIIkSUcBayHEqcbx74Db+ZMDMz+/N7CyHkhS0r+Y5vMzmy5PZ8+FPCYHd28RfXej9vx5Krf9hP0jj2DS+OW+iuKaYl49/iq+tr4sGLKgS/av6ldG79rOlTotRpKMsBG3kkowLvk1hIcHN9x0jI1xmDMH6wkTKFj6DsrPvsZkXyR9Fi/GPOxW0NbD1ifA81YY0lwiSq/XcOnyQgoKTuDuPosxfot4VpKh0Ws6zOJd/7pSXcm+jH3sTtvNHX538FjwY/Sy6IWb2/2kpa1ApUrBwqKvYW98wBSIXQ9px6DfNSFvb29voqKi0Gg0GBt3vBQW1NsGE7mMsxnlBgdmVSW1HPx3Io4eloyc2a/Vm/qAYb2IP5jN6R1peA9yRNaDXUuewaHIjIxIiz3b6cBM+VtOg/zSzT1zQesslIqLyCQTTMu9KPrqPE5zg3qEUy2yrJrtRRW85NULb3PDM6WDbSzYHdaPB86ncc+5VD7z78N0ZzuURxq0LC1Hjup2X6+Hk+M4UtM+pK4uH1PTa5/Xi7/lIpNJ+N9i+MNFezC3VuA3xIXLp/MZOt0HU4sbX1aWmZpi6u/ftTqzvQuh4MIN+9AMvQbCxJZLk9cjNzcXDw+Ppr/d3d2JiopqNmfx4sWMHz+ezz//HJVKxcGDB5u2aXV6lGotJnJZq7VlmzZt4t577226hrRnKz09ndDQUKytrVm6dGlToNOWrbag1+t58cUX2bBhQ5PG5+9RUVHBrl27ePbZZ1v1a/ev+9HqBRYyo7+UX9efr+7EjVy9XYQQ+QCNv68+prsB16vT5jSOtTee08p4C0iS9JgkSdGSJEUXF/dst6QkSbj2up1hQ/dxT4iEh1UOb/58gqKy1ust/goQej0FS5Yid3LC8Yn5zbbp9DoW/raQWm0ty0cux0zeucyApq6O+P17+PcLj7P9gyUUl5WhN7Vg7OQpjH34cS4W1RHu2ZJY1tjNDY8vV+H+xUp01dVk3n8/+W8uQhezDWpKIbR50b9OV8P5C/MoKNiOj88L9PN7q4nN31hmjI2JDb0te9PPrh8hziEMdxvObV63cYffHcwKmMXjgx7nhYgXWHTTIpaPWs6eO/dwV7+7+DnlZyb/NJkPzn6Auf1tyGQKsjtDneEzEhRWcHlXs2Fvb290Oh3Z2YYJMivkMgZ52BKdaVjdi1ajY9+aBn3KCY8NRN4GSaTMSMaw6T5UFNZw6WS+Qba7ChNzC9z9A0mL6RyfmU5ZjyqmCIswF4ysOk903BOoKD+DtU0ILo+FA1C8+jz1uTdOZ3I91Ho9rybl4G2m4Kk+nc9mepubsCvMj0FW5sxLyGRlZiHKo0cxDQzE2KVns6NOTuMAKCm5duPS1uu4fDIf7xAnLGxuTDT9egwa4462vqGhoLtgFhJC7YULCM0fR8R8I2itguf319RNmzbxz3/+k5ycHPbs2cOsWbPQ6xu4+YqVaoQAM0XrOZcffvihmTB3W7ZcXV3JysoiLi6OFStWcP/99zdlitqy1RZWrVrFpEmTmgWc10Or1XLffffxzDPPNGUKf+/Xww/NRq/X4+vh9pfy6/pz353oifaG1sJU0YXxloNCrAHWAERERPwhNWgmJs6EDvqKRWInj22W8eaWtbw2qR99PB7+y4kdV/70E3UXLtD7g/cxsmxOPbH6/GrOFJxh6S1L8bH1acNCS1SXlRD/627OH9hLnUpJL18/Jj/zMpeLy6lMSCAsYjCFVXXklNfyz5u92rRjNXYsFsOGUfzFKsrWr6d6NzgP7o2N75imD4BGU078uUepqjrHgP7v4OY2swtnoTmczZ15Y9gbPBz0MF+d+4rvL33Pj0k/8oqnL+Rvw9fnRYyNrTs2JDcBv3FwZS/odQ3LmzTUL0iSRHp6etOXtyNEeNqxJjKN2npdh2zcv/2QRHFWNZOfCMbGqf1g2nuQI718bDjzSzr9hvbqUEz6RuATNoSj331NZVEBNs6G1YopT+WDVo/lDRaLdxc0miqqlYl4ez2NsYsFzvOCKf76AsVrzuP4cCAmXt3Dr7Yqq4jUWjU/DPLBtIuZTAeFnC2DfHnmchYr4y8z5tw5HJ54olv8aw8WFr6Ym/tQXHwAd/cGObeU2CLUNVqCRnbv/9HR3Qq3/rZcOJrDoH94YNQNWV/z0BDKN2yg7koSZkGdyO52kNnqKbi7uzd7yMvJyWmxXPbNN9+wb98+AG666Sbq6uooKSnB3sGRUmU95gqjVuWKzp07h1arJTw8vENbzs7OmJg0BN3h4eH4+vqSlJREREREm7bawqlTp/jtt99YtWoVSqWS+vp6LC0tmxobHnvsMfz8/JqK9Vvzq7auDlV5KdbenmBm9pfx6/rz1Z24kU9+YeMSJY2/ixrHc4DrQ1B3IK+DcfdWxv8ykCSJcaHTmRHuwoHMERyJW09M7ExUqr9Ot6auspKiFR9jFhaG9dSpzbZF5Ufx1bmvmOY7jel9pxtkrzAthT0rl/P1U3M4u2MbHoHBzHz7A+5/ZwVe4UNJSEggKCgIU1NTYhuzP60Ry14PmYUFLq+8jPf6L1GY15J/DLIenoM6NZW6ujyiY2aiVCYwcODKbgnKroebpRtLblnC9unbGek+km+y0tHra/kp9kVqNAZK4QyYDKriBiWARpiYmODm5tYpotnBXvZo9YL47Ip25yWeyCPxRD7hEz3xCu6YVkKSJG6605eaynrOHzYsg9dV+IRdVQEwrDtTX69DdSoPU397jJ3Ne9I1g1FZGQ0IbO0a+MvkjmY4PT4IIysFJd9cpC75xrv5MmvVfJpZyDRnW0bZG/AA0A5MjWR8FeDJ6/mpSELwvrsfSm3PSw45OY6jvOI0Gk1DZuLisVxsXcxx62fbwZ6dx6AxHijL1aTFdc+KiFlTA8B/B23G4MGDSU5OJj09nfr6en744QemTZvWbE6fPn2alt4uXbpEXV0dTk5OFCvV6IXA2qz1ZeBNmza1yCS1aau4uEluLi0tjeTk5GYPnq3Zagvff/89WVlZZGRk8NFHHzF79uym4OeNN96gsrKSTz75pE2/EhITqaurw7NXr7+UX9efr+7GjQRmO4GHGl8/BOy4bny21IBhQGXjUuevwHhJkuwkSbIDxgO/Nm6rliRpWGNH5+zrbP1pUMUUUvqfxGbCx69ODsHO3JQfM16hWpnGmbNTyMz6unPUCz2E4s9XoquooNebbzRLfZfUlrDwt4V42Xjx+tDX27Uh9HpSoqPY/PZC/vPqc6ScPU3I+Mk88ukapr34Gm4DApAkifPnz6PRaJqeUmIyy1HIZQT2NizDYKo6jefYEnq98jR1ly9zZd50zhydiFpdQMigdTg73db1E9EBvG28+XDkh3wy4SdKhB1UHmHitttYn7CeOm0HYsp+40Fm3IJs1tvbm7y8PNRqtUE+hPVpCGCjM9qmzSjOqibyhyTcB9gxZKrhGc7efW3xCnYk9tcs6pQ9t3xj5+qGnaubwYFZTUwh+hotVj0ov9RZlFdEIUkKbKxDm8bktiY4zQtG7mBKyboEahNLu2xfCMGrSTkYSRJv9+2emjqZJDE68Rz1Do5stnXmjrgUCtQ9u0zn5DQOIbSUlh6lOLuawvQqgm5165FGKM+Bjlg7mXXbg4WxqytyF5ceVQDQafTdRo4rl8tZuXIlt912G/7+/syYMYPAwEAWLVrEzp07AVi+fDlr165l0KBB3Hfffaxbtw6dXlCqrGfyzYNY8PJLrFu3Dnd3dxITE5tsb9mypUXQ0potSZKIjIwkODiYQYMGcffdd/PVV19hb2/frq2zZ8/i7u7O1q1bmTdvHoGB7Wcoc3JyeOedd0hMTCQsLIyQkBC+/vrrVvy6n7dXrcZKbvQX8+va+ep2CCE6/AE2AfmAhoYM1xzAATgEJDf+tm+cKwFfAKnABSDiOjuPACmNPw9fNx4BXGzcZyUgdeRTeHi46ElUn8oV2QsiRdXxnGbjW6OzheeCX8SGExdF/LlHxcFDPuJs9N1CqUztUX/aQ+3lKyIxIFDkLV7cbFyn14lHf31UhG8IF1fKrrS5f31trYjdt0t88+yj4qMZk8Xq+f8UZ3ZuE7XK6hZz9Xq9WLVqlfjyyy+FXq8XQghx+xfHxV2rThjmrE4nxMcDhfj3ZCGEECWZh8WRvQPE4Z98RML9t4rqyEgD3/WNo6Bwtzh4yEcs2n+7CFoXJMZsGSM2X94s6rX1be+04U4hPgkWovG9CyFESkqKeOutt0RSUpLBxx6/4piY/U1Uq9tqlfXiu9dPiHULj4uaKi0d+FMAACAASURBVHWbNmIqlWJtdpHQXeeLEEKU5FSLlY8fEse3Gu5PV3Bk/Vrx8f3Thbq2pt15ep1e5H1wRhSujGv6zPwVcObM7eJs9IxWt+lU9aJgZZzIfjVSqOILu2T/l6Jy4XI4TqzO6tr+rfqlVovLoWEi781F4mBJpfA5dk6EnrgoEqvb/x/cCPR6nYj8bag4f+EpceQ/l8SXTx0Rtcp2viM3iPhDWWLlvEMiP62iW+xlP/ucSB49psN5iYmJnbatqdeKwsxKUV1W2xXXug15FTXiXHa5qK3X/ql+9ATy6+pFfKVKaHR/nWuHIWjt8wRECwNiLoMyZkKI+4QQrkIIYyGEuxDiGyFEqRBirBDCr/F3WeNcIYR4UgjhK4QYKISIvs7Ot0KIvo0//75uPFoIEdS4z1ONb+BPhcVQV0wH2FO5Nx1Ngapp/K4wN4Z42fPRwVzcfT4nIGA5KlXqn5Y9E0JQuHQpRlZWODd2jlzFNxe+4VT+KRYOWUg/u5Y8RNVlJfy2cR1rnvgnh7/9ChMLSyY/+wpzP/+awVPvxNSipURSTk4OhYWFREREIEkSdRodCblVHS5jNiHjN6jIhLDZlJQe5XzaUyhsXAl2+RiTMguyH32MnOeeR1NY1LGtG4ST4zhMTHpxu6MV3972Lb0terPk9BKmbp/KjpQd6PSt/C8HTIHyDChMaBry8PBAJpN1ajkz3MuO2MxydL8TNBd6wcF1iSjL1dz2aBBmrRTJ1+n0LE3NY0pMMm8k5/J1TvNlHwc3SwYM7cWFo7lUl3WQBbwB+IQNQafVknXhXLvzahNK0ZXWYfkHyi91BK1WSbUyoU0ZJpm5MU5zg1B4WlP2wxVUZzun5ajS6ngzOZdAS1Meceu+pY6aM2fRN7L9j3WwZkdoX/QCpsYmc6ysZ2S5JEmGo+NYigpOk3SmAL8I527pmmwL/je7ojA14vzh7iGcNQ8NQZOX1yPXlJrKehBQW61Br/9zblsNmpj12Jor/mdY/q+HUqvDzEjWat3c/yr+Zv5vA5IkYXe3HzJTOaWbLiM0+qbxpXcEoazT8v6+y02dm/b2w0lJeZeY2JnU1Bh+g75RVO3ZQ83Zszg99xxGttdqPmIKY1gZv5KJ3hO5y++upnFNXR2Xjh/lp/cWs/bJRzi78yc8goKZ+a8PuX/pcgbcfGu7pKExMTEoFAoGDhwIQEJeJfU6PWGGBmZxG8DEhnx7wfnz87Aw9yU8fAsON0/De8d2nJ59BuXhw6RNmkTZhv8gdD0X6Mpkxri7PUBZ+Qn8rWz5buJ3rBq7CmuFNW+ceIM7dt7Brxm/ohfXdd30nwRIzZYzFQoFHh4enawzs6NarSWpsPnNNGZfJpkXShl+jx+9WhH3jquqYXx0Eiuzirjf1YFxDtYsSc3nfHXzOrkh0xqWP3tS4NxtQAAKM3PSYtvuzhRCoIzMwcjBFLNAw4lIk8uT+fDsh0z5eQqHsw53h7vNUFkZgxA6bO3aFi6XmchxfDgIEz87yrclU30812D7H2UUkKfW8H4/j269oSiPHkUyMWli+w+yMmd3uB8epgoeOJ/KxvyuL722ByencZSnDUSj1hN4a882byhM5fjf0pvUmCKU5Tf+YNFTgubaeh11Kg0KUzlCiB4tHWgPV2vLnDtJWP3fAJ0QqPR6rP7HRct/j/9f77YTUKenU7F7B/b39ENbWEPlvms33X4uVswZ4c2W6ByiM8owMXEmeODqpuxZ1JnJZGV90+PZM71KRdEHH2IaEIDtPdcY6cvrynkl8hXcLd1ZNGwRQq8nPS6aPZ9/xJePPciezz+iJCuTiKl3MuezNUx74TXc+vt3mM2ora3l4sWLDBw4sKljJ6ax8P9q3VT7BsohcSeZYSEkJr2Gre1gwsK+x0TRUNguUyhwnD8fn107MQsJofCdd8iYcS+1Fy528Qx1jN6970UmU5CTswFJkhjhPoLNUzazYtQKZMh46dhL3PvLvRzLPtaw7G7l0qAE8Ls6My8vLwoKCqitrTXouBGeDXUR19eZZSeWEbUrjX5DXFp0vKn1epal5jE5JgmlTsemYB8+GuDBp/59cFTImZ+Qieq6QnAre1OCRrlx5XQBpd1M/3AVRnI5XoPCSIuLRrTRMl6fUUV9djVWw92QOghQKtWV/HD5B2b+MpM7d97JxksbUWlUvHniTQpVhd3qe3nFGSRJjq1NWLvzZAojHGcHYBboQOUvaVQdzuqwnuiSspY1OcU84GpPhE37nGh6oUejN+yGLoRAeeRIA9u/2bUOXTdTBTvD/LjF1ooXLmfzXlp+twqCA9jZDqMidQyWTlW4eN1YE4MhCB7tjhCCC8cMD4bbgqm/P5JC0e0NAKoKNZIkYe1oirGJEbXV9d1+3juC5v9BtgxBq/Jl/8v4OzBrA2dWHWDvz+VUnt6H5c29UZ7Io+7KtZvos2P96G1jyus/X0Sj0zfjPbO3H05yyrIez56VfLUabWEhLm+8gdSY5dILPa8df43y2nLe6PMMZ77/ntXzH+Kn9xaTFneWAcNHMuOtd3l05Tfcev8/DaY6ADh//nyLVuSYzHL62JsbJC8kzm8luY8RKcYJODtNJGTQN8jlVi3mKTw98fh6LW4fr0BTVEjGjBkULFmKrrr7l2oUCgdcXKaRn/9TU9eZJEmM8xzHtmnbWDZ8Gcp6JU8dfopZe2cRlR/VsJxZcKFhSbMR3t7eCCHIzMw06Ljudma4WJs08ZlVl9Wx/5sE7F0tGPXAgGZBcnxjluyzrCLudbXn6JABjHZouDnaG8tZ6d+HtFo1b6Q0v4lFTPDC2MSI0zt6LmvmEzYYVXkZRRmtH6M6MgeZuRzzcJdWt+v0Oo7nHuelYy8xesto3ol6p0HLdfACDs04xLoJ69DoNbx54s3mmcsbREV5FFZWAzEy6rhDVJLLsL/fH/NQZ6r2Z1K1L6PNG7BeNIiU28iNeN23/YL/QlUhd+28i7m/zm192fx3UCcno8nNxXJ0SxZ7K7kR/wn24X5Xez7JLOTJS1mou5FfqShDjbqyNzY+B2mDzahbYe1ohvcgJxJ+y0VTf2MPuJJCgWlQULcGZhq1FnWtFnMbBTIjGWZWCnRaPera1nVNewolSjXifzRbBqDU6ZEksPg7Y/Y3AHrdPYUqWx8O7FOhLj+L3MWcsq1J6JT1AJgr5Lw1LZArhdWsO5HRtN8flT2rz8igdN06bKZPxzzsWlfZt5ErUR65wOxT/Tn54eecP7QP9wGBTHvpdR5f/R/GP/Y0HgEDkVqRp2gPQgiio6Pp3bt3E6+OEILYrAqD6sv0ei2X8j4jy8McN7cHCQr6FJms7YuJJElYT5yI75492D3wAOUbN5I6aRJVe/Z0+1Oph/ts9Ppa8vO3Nhs3khkx1XcqO+/YyaKbFlGgKmDu/rnMLT9NvIkCLu9umuvu7o5cLjd4OVOSJCI87YnOKEen0bNvzUV0Oj0T5w3EuFGqqF6v5/20fCbHJlGl1fF9sA8fD+iD9e+eHm+xs+I5Txc25ZexvfAaxYOppTGht3mScb6EvJT2qTm6Cu/QCJAkUlshm9UU1VB3qQyLm3oj+x2nWkZlBp/Gfsr4beOZf3A+UflRzOg/gy1TtvDjtB95MOBB7E3t8bT25KWIlziVf4pNlzd1i886XQ1V1RfarC9rDZKRhN09/bAY5kr1sRwqdqQ269i+is0FZZypVPGGb2/sjdumicyqymL23tlkVmUSWxTLtuRtHfqgPHoMAMtRI1vdbiyTWN7fg1e9XfmpsJyZ51Kp0HRPoJAQmYtcIbDofZiqqp7rcLweg8a6o1ZpSYrqXH1fazALDaEuMRG9gZ3THUFVUY9MJjXVgJqYyzGSy6itqu8W+4bgarbM5n80WwZQrdVhYSRD9hepTf2j8Hdg1gb8hvZm3MMBVNl4c2BfNcLsEvo6LeXbkpsCg/EBLowd4MzHB5PIq7i2hNXT2TMhBAXLliFTKHB+6UVUFeXE7tnB2pfnUblqP4NSbOnt6s34x59h/pr/MPWFV/EbfBNyAySD2kJ2djbFxcXNsmU55bUUV6s7rC/T6Wq5EP0A+Ta1eBvfQv9+iw0m5zWysqLXG6/jtWULxk7O5L7wItlzH6XewMyUIbCyCsTWZjDZORtaDaCNZcbc0+8edt+5mwWDF5CsymVW7148eWUdl0ovAQ1t7h4eHp0StA33tCO3opZfv79EUUYVYx/yx9alIYNzvrqG26KT+DizkLtd7Dk6uD9jHdpeQnrRqxcR1ua8fCWbzNprN59BYzwwt1Fw6qfUHllmMbe2wdWvf6u0GcrfckEuw/KmBtkeZb2SbUnbmLVnFlO3T+Xbi98ywH4AK0at4NA9h1g4ZCH+Dv4t7NzT7x5Guo9kRfQKUspTbtjnyso4hNA28ZcZCkkmYTvdF8tb3VGdzqf8xySE7to5LdNoWZKaxxAbC2b2sm/TzpWyK8zeO5tabS2rhq8izDGMT2I/obS2/fow5ZEjmAYEYOzSevYRGq49z3q5sCrAk5jKGqbGJjf7PHQFdUoNKTFF9BvqgpFCT3HxgRuyZyhc+9ri6GHJuUPZN/zZNQ8NRWg01CUkdjy5A9TXaqmv02JuY9KkEypJDUGaRq1Do/5jGsD+17NlGr0etV5g1U7N8/8q/g7M2kFTcGbtzcFjdQjzK9RdKkPV+AQnSRKLpwWiF4J/7Wr5he+p7JnyyFEqjx+n8o6p7Fj7OavnP8SR9WvJqcomaZCOBz/9ghmLljFw9HhMzLtH9y86OhoTExOCgoKaxq7Wl4W3U1+m0VQQFz+bkupo+qfW4RPxaZc688wGBuG1dQsur79ObXw8aVOnUbxqFfr67nlCdfd4iLq6bEpKjrQ5x8TIhAcDHmTvnXt51iaYOH0NM36ZwQtHXyCtIg1vb28KCwtRqVRt2rgeg73sCag3Iv10ISHj+uAb6ky9Xs8H6flMjEmiTKNlw0BvPvXvg0072RcAuUxiVYAnAE8kZqJpzOYYmxgxeLI3BWmVZJwvMfBsdA6+YUMoTEtGWX5tqV9XXY8qthDzcGeiq+N47bfXGL1lNItPLaayvpLnw5/n4N0H+WLsF4zzHIfCqG2JJkmSWHzzYiwVlrx6/FU0uhsrsi6vOAPIsLXpmB28NV9sJnphPc6Tmtgiyn64jNA2LBkuS82nUqvjvX7ubT7hxxfF8/CvDyOX5Dxq/Sj7N+ynT3IfajQ1rIhZ0eZxtWVl1MbHYzlqlEF+3ulix+YQX4rrtUyOSSa2yrDPZGu4dCofnVZP8Cgv7GyHUlzyxwRmkiQxaKwH5QU1ZF9qm/PPEHRXA4AQAmWFumH50rL5g66ppTGSJFFzg1mzffv20b9/f/r27dtEeHo9srKyGDVqNGNuGcqM24Zz+MCvABw4cIDw8HAGDhxIeHg4hw9fa5rZtGkTAwcOJDg4mAkTJlBS0nAtWLx4MW5uboSEhBASEsKePXuABvLVq2MhISHIZDLiG8/d66+/joeHB5aWLbv2AX788UckSWoSBe+qX308PJgxfBj/GDr4L+VXa+eru/F3YNYB/Ib2Ztwj/lRbe3H0ItTXnadydxqaooYuOA97c54e48e+hAKOXG7Zjt2d2TOdVktK1El2f/YBh4J8+O3CWcrychk87S5yZ7ixc3g+Tz/2Ib16ed7w+74eNTU1JCQkEBwc3FT0Dw2BmYXCiP69WtaJAdTV5RMTO5OqqgsMTNHibjcBzAzs3mwFkpER9rMexGfPHizHjqHks89Jn347qtOnu2zzKq5SZ2TnrO9wrrmxOXOHvsK+nFzmOd/EidwT3LHzDvZX7QcwOGvmrJcYX2NMvZ0xN93uw8XqGibGJLEio5A7Xew4NmQA4xwNlwXqY2bCh/09iKmqYXnGteUf/1tcsXUx59T2tB5p6b+qApAe38SMQ/7RywidnudqFjF3/1yOZB9hqu9Uvp/0PTum7+CRoEdwMjecRsLRzJG3b36by2WXWRm/8ob8rag4g5VVYKv1jYZAkiSsx/bBZrIPtRdKKN2QSHRpNf/JL+VRdycCLFuXzjqZe5JHDzyKhWTBiNwRpJ5JpX///sgr5Qw3Gc7O1J3EFMa0uq8yMhKEaLW+rC3cZGvJrjA/zI1k3BWXwp7izi9nC70gITIXV18bHNwscXIaR01NOipVaqdtdQV+4S6YWSs4d+jGqDPkjo4Ye3jccJ1Zfa0Wbb0OC1tFi2YWmUzC1NIYdY0GnbZr9X06nY4nn3ySvXv3kpiYyKZNm5qRxAIsXbqUCVNvZ8u+SDZt3MQTjdJcjo6O7Nq1iwsXLrB+/XpmzZoFNGg+Pvvssxw5coTz588THBzMypXXvkPPP/888fHxxMfHM2nSJAAeeOCBprENGzbg5eVFSGNwO3XqVM6cab0Tu7q6ms8++4yhQ691O3fVr0eeepptJ05zLi7uL+VXa+eru/F3YGYA/Ia6MX5OANVWnpwoMqUmJ4qyTdeelB8d4YOvkwWLdl6kTtN6Nqwpe+b/ESpVisHZMyEEuVcucfCbL1n9+Gx2rFhGkRH0Dw5l5tsfMPfzr8kYJOOA8iQvhL9AkGNQu/a6gnPnzqHT6Vroj8VmlRPSxxajVrrtVKpUYmJmUFeXT4jVP3HOr4CwWd3ij7GLM+4ff4zH2jUIrZasfz5M7iuvoC3tOlWATCbH3e1BystPolQmdbxDr2CsrTx4qrySvXftZZb/LH4t/xWtpGXr6a0UqNqvi1HXajnwdQLCWEakk2BFVhETYpIortfy3UBvPvf3xLaDLFlruN3Fjvtd7fk0s5Dj5Q3NEkZGMoZO86E8X8WV090vcO7YxwsrByeSo0+zK3UX83fPo/pUHietzmHiZMl7I97jyIwjLLppEcFOwV3mMhvlMYq7/O7i3xf/TXRBdMc7tAKdTk1VVXyn6svagtUIN2zv7IsyuZwXz6biqpDzklfrzTT7M/bz5KEnsdZaE54UjouZC3PmzOHee+9l2LBh2F62xcnEiaWnl7bapak8chS5kxOmgQGd8tHPwpTd4X4MsDBjzsUM1mR3jssr50o5lcW1TRQZjo5jAf6w5UwjYxkDR7qRlVBKeUHXs37QkDWriY/r8rLo1WyZkVzWJo+beWPNWW1117JmZ86coW/fvvj4+KBQKJg5cyY7djQXwhFAYWkFtuYKamuUTTW/oaGhTa8DAwOpq6tDrVY3kZaqVCqEEFRVVbXQ32wPv5c5GjZsGK6urq3OffPNN3nllVcwNTVtGuuKX0KIhmVMuVGb14s/w68/Cj0hYv4/ib5DegOC/d/A6epMhp45gomfLbaTfFDIZSy5PYj710bxxZEUXhzfv1UbkiTh6noH9va3cPnKGySnLKOoeB8B/h9gbu7dbG5pbjaXjx/l0oljVBYWIDdW4B0UjM2uX/EKG4znG0sAuFhykRUxKxjtMZoH/R/s9vd9tejf3d2dXr2u3XRUai2X8qt4anTfFvtUVsZz7vxcQEZ42EasfloItp7gdWu3+mY5YgQ+u3ZSsno1pV9/g/LoMZxffBHbe+7udHMDNFBnpGd8Rk7uBgb0X9L+ZElq0M6M/hZ7yZiXBr/E7MDZfPntl1QVVDH5p8ncO+Be5gTNwcGsOX+XEILD6y9RVVJH5TBb4hLzOJWSx91uDizxc8OuCwHZ9Vji58aZShVPJWZxaHB/HBRyfMOccPay5syudPwiXJB3k8C5EIL44nhKe0N5XBQbHbYyq+4OrPQWjLhrMvcOeLpbjnMVrwx+hbMFZ3n9+Ov8OO1HrBSdy3pVVcWj19e3y1/WGVgOcWW9vpYrtVUsT9ViHqqH3zVnbE7czDtn38G+zp6RFSOZMGECERERyBo/o6NHj+by5cuElIVwwOIAGy9t5KHAh5r2F/X1qI4fx3rSxC59rp0UxmwL7ctTiZksSskjq66et/u6YWRAgHwxMhdTC2N8wxqym6amrlhbBVNccgAvr8c77UtXEDjCjei9GZw/ksPI+1q/thoCs9AQqnbtQpObh8K9fS6298+8z+Wyy83G9DqBTqPHyFiG7ELb506r0SP0oqmJ5yoG2A9gwZAF7R43NzcXD49rktLu7u5ERUU1m/PECwuZcfsUtn63FpVKxcGDB1vY2bZtG6GhoU0rHF9++SUDBw7EwsICPz8/vvjii6a5K1eu5LvvviMiIoLly5djZ9d8VWPz5s0tgsPWEBcXR3Z2NlOmTOGjjz5qdY6hfukEbFzzFXt/2MjQwYP/Mn5Bx+erO/B3xqwtqKshq/kSWd8hbtw2x59qK0+ihB1F3+9oEjq+2deRO0Ld+OpYKqnF7fNGtZU9qy4rJvqXn9mw8FnWvTCfqJ+3YuviyoQnnufxNf8hrKASF1UdvRc2fLmr6qt46dhLOJk5seSWJT3Cqp6ZmUlpaWmLbNm57Ar0ghaF/6WlkcTGPYjcyIqI8C1YacwhPRJCH4Qu3FQ6gszUFOdnn8Vnx3ZMBwyg4K23yLzvfuouX+54599BobDHxWU6+fk/o9FUdryD/xTQqSGl4cLobO7MP0L/gZXGiom9J/L9pe+Z+NNEPov9jEr1NXtxB7JIiy9GM8qZb8wbnqxfsbVnZYDnDQdlABZGRnwZ4EmZRssLVxp4tyRJ4qY7fFGWq7lw9Ma5oQpVhXx94WumbZ/G7L2zOW2ejFwn8aHX6zxQPQWFpzW9Bxiu8WkozI3NWTZiGYU1hbwb9W6n92+oL5OwtRncLf4UqDV8XK9klMKUW68oKV5zAV1jtkQIwXuH3mPp2aU41zjzpMuTvPDkCwwZMqQpKIMGguKpU6diVWRFgEkAX8R/0SzjWhMdjV6l6tQy5u9hbiRjbZAX89yd+DqnhDkX01F1QN6sqlCTfq4E/5tdkV/X9efkNI6qqnjU6u7llmsL5tYK+g3pxeVT+dSpul5faH6DguY6rR5JBjKj9q+zRkYSiIZArrNoLZt3/XVdo9OzcdMmZj4wi5ycHPbs2cOsWbPQX0eNkpCQwIIFC1i9enXDPhoNX375JXFxceTl5REcHMy77zZ8d+bPn09qairx8fG4urry4osvNjt2VFQU5ubmzWqLW4Ner+f5559n+fLlbc7pjF/3Pfoov8RfJCYu7i/lV0fnq9tgiG7TX/Gnp7Uyxc/zhVjaS4i8+BabUqJyxBeP7Rfr7/tGJM39TGgbdeOKqupE0Fv7xH1rThmsCVhVniEiD90uDh7yETu+DxSfP/oPsWHhcyL6l+2iuqy0aZ7y1CmR2H+AKPriCyFEg2bl80eeFyHrQ0RcYVw3vOHWsXXrVrFs2TKhVjfXbPzsYJLwXPCLqKi5ppmXn79DHDrcT5yOmiLq6ooaBg8tEeItGyEqsnvMx6vQ6/WiYvt2ceWmm0ViQKAoeO99oVMqO2WjqipBHDzkIzIy13Y8WasR4j0vIX6c0zSUm5sr3nrrLXH+/HmRWpEqXjr6kghaFyRu2niTWH1utUhJyBMrHz8kXn33hHA5FCvmxqUI74W/iOX729Yy7SrWZBUJl8Nx4pvsoqaxnZ/FibXPHxN1qs5rHdZp68TetL1i3v55Inh9sAhaFyQe2vuQ+CnpJ1GpLBefPHiniPpko8heEClqLpZ051tpgS/ivhBB64LEvvR9ndovJvYBcTpqSrf58djFdOF5NF6k19SJ2qQykfPGcZH/4VmRl5It5qybI4LWBYnbv75dpGZ0rKW7Y8cO8fLSl0XYd2Hi+SPPN43nL31HXAoeJHQ13aOHuTa7SLgejhO3nb0iitRtfw7O/JImVs47JMoLVc3Gq5VJ4uAhH5Gd8323+GMIirOrxMp5h0TMrxldtqHXaMSl0DCR/68lrW5vTyuzpkotCjMqDf7elOYpRUlOdae1YU+ePCnGjx/f9PeyZcvEsmXLmv7OLa8Rvv0GiOTU9KYxb29vUVjYoMeanZ0t/Pz8xPHjx5u2nzlzRowZc00r9NixY2LixIktjp2eni4CAwObjT333HPinXfeadVXCwuLptcVFRXCwcFBeHp6Ck9PT2FiYiJcXV3F2bNnu+RXqqquSf/1r+TX9WjNr+vR41qZ/y8x9i0ws4eNM6Eqr9km38bMmdLKg1MqS7KWbEAIgZOVCa/c1p+TqaXsPJfXhmHQaTWkREex65P3+fap5zmzup7iGH8snAUB9+Vw6/wgwiZNwdKuoeVeaDQULF2Ksbs7DnPmALD5ymYOZB7gmbBnCHEO6ZFToFKpuHTpEoMGDUKhaN41F5NVjp+zJTZmDbUWWdn/JiHxeWxswgkP24iJiRPodRC/EfqOBRv3HvHxekiShM306fju2Y3tnXdS9u9/k/XInE51blpZBWBrO4ScNqgzmsFI3iDRlLQftA3H6NWrF6ampqSnp+Nj48OHIz/kx6k/Eu4cztdRG/jpq3OUWsrYM9SCbwZ6szbEF39Xa2Iyb6zrrDXMdXdkrL01b6fmkahsoHMZdrsv6hotsb9mGWRDCEFCSQJLTy9lzJYxvBz5MqmVqcwdOJfdd+xm3YR13OF3B9YWtvQJDMYixxS5oxmm/m3TRXQHHg1+lIGOA/nXqX8ZrAqg19dTWRnXLfVlAMfKqtlRVMEzni54mZlg6meH9ex+HK++wPw9TxFFFCNtR7LloS34eHacPRw3bhzOJs6E1IVwIPMAx3OPN7H9mw8b2ozt/0Yw192Jfw/05oqqjkkxySSpWsoe6XV6Eo/n4eFvh61zcxJeC/O+mJl5UVy8v1v8MQSO7la49bflwpEc9LquFdZLcjlmwcGdzpgJvUBVqcbYxAiFmWEZbXPrBsLZ+k4Szg4ePJjk5GTS09Opr6/nhx9+YNq0aUBDtqxMVY+HhwfHI48CcOnSJerq6nBycqKiooLJkyfz7rvvcssttzTZdHNzIzExkeLiBk3dAwcO4O/fQEuTn3+t5vTnn39uloHS6/Vs3bqVmTNndui3jY0NJSUlZGRkkJGRwbBhw9i5cycRERGdc4aq/gAAIABJREFU9ksvBBm5OVg1lgT8Vfzq6Hx1J/4OzNqClQvcvxnUVbBpJtQ3Lzz1HeLOhDn+KK3c+S1bRt7nDeSk9w/1JNjdhqW7L1FVdy3tLvR6ci4ncGDtSr6aN5sdHy4h++I5gsaM574ly7n3pV0MH3EEB4cRLTo3yzdupD4lFZdXFyIzMeFS6SU+OPsBI9xGNKtF6W7Ex8ej0+mIiIhoNq7XC+IaiWWFEKSkfkhy8lKcnG4jZNC/r3W7pR6GqlwI7Z6if0NhZGuL65J/4fbJx9SeO0fB2293quDXw/0h6upyKCkxQKPRfwqoKyEjEgCZTIanp2czotn+9v15YvD7TMp+B7lewfawNGxK3kRVth+NTkOEpx1xWRVou3jDaQuSJPGJvwc2ciPmJWRQo9Pj5GFFvyEunDucjbK8bX6rktoS1ies586ddzJz90y2p2znFrdbWD1uNfvu3MfToU/Tx7pPs336ed+EjZEjUpBZh/JLNwpjmTHvjni3U6oAVVXn0evrOs1f1hrqdHoWJmXjY2bCk32cEUJw8eJFvtq5jm+dt5JqncqdVeNYMfQ9jOWG8QeamZkxZcoUeuf2xlnuzLKoZSiTLqHJycHqBpYxW8Ntjjb8HNqXOr2eqbHJTY0iV5FxoRRluZqgW1s+UEmShJPTPygvP41W2zPC6a1h0BgPlOVq0uK7TvtiFhpC3ZUr6GtqOp7ciNrqevQ6gYWticHlIibmcmRGsk5TZ8jlclauXMltt92Gv78/M2bMIDAwkEWLFvH95m0IAR8vX87atWsZNGgQ9913H+vWrUOSJFauXElKSgpLlixponMoKiqid+/evPXWW9x6660EBwcTHx/Pa6+9BsArr7zSRAtx5MgRPv744yZfIiMjcXd3x8en+UPFK6+8gru7OzU1Nbi7u7N48eJ231Nn/arR6Vnx5huMjwj7S/nV0fnqTkiduWH9lRARESGu8pH0KJJ+bQjM+k+CGRta1EmlRmXz6zeXsVTlcttUR1xmTuFCTiXTvjjO7GGePB1mxaXjR7l84hhVxUXITUzoGzEM/xGj8BwYipG8+ROYEIKCgu0kJf8LvV6Nl8vjqGd/h3lIGB5rVlOjrWHGrhnU6er4ceqP2Jl2f+HhVT8+//xzLCwsmNOYpbuKlKJq/rEikvfvCmKg5Zfk52+ld++ZDOj/r+bEsZtnQeYJeOEyyNvmqepJFH36KaVffoXLG29g/+ADBu2j12s5eWoU5uZehIX+p/3Jmlr4wBcG3QtTGr6kp0+fZt++fTz33HNYWtvwZXYRMT+lMvhKHQ73eOEbWMpnsZ8RXxyPm6UbQy2fYP0RI3Y9NZyB7obTYxiKyLJq7j2XyqzeDnzQ34Oqklq+f+s0A25yZfSDA669FZ2GyNxItqds53jOcbRCS7BjMNP7TmeC9wSsFe1rJBasiUWZXETZzUqG3HF3u3O7C1uubGHJ6SUsGLyABwPab37JyFhFatpyRgw/i0JxYxm95ekFfJhRwOZBvgTo6tizZw8pGSnEecSRaZTJM/2eYPLhUNALHB8ZiMKtdW6l1rB161aOZhwl0jmSdzOH4LvxJH2PHsG4l+HyaYYiq1bNA+fTyKit5+MBHtzdSIy76/N4SnOUzF52M7JW5HAqKqKJib2XoMBPcXGZ0u1+tQa9XvD9W6cxt1Jw1yud56ADUB47Rva8x+mzfj0WQ5sH6JcuXWrKjFx/zNJcJcYKoybyZ0NRU6lGWaHGrpdFi0aAzkKj03OloBobM2M87Dvnx38bCtT1FKq1BFqaIe/hB7yeRGufJ0mSYoQQEW3s0oS/M2Ydod9tMP6dBtHqQ2+32Ow71IPx9/dFadGbX3eVUrz7IF7mGsa76PjuZAYfvvYWZ3duw97Ng0lPvcj8Nf9h8jMv4xM6uEVQBtc6N4cN/RV7++Gk5X9K0bxKrF9uyDq9feptcpW5fHDrBz0WlAGkp6dTVlbWIlsG14hlLdWfkp+/FW+vpxnQf2nzoExVAlf2QvDMPy0oA3B6+mksR4+m8N13UUW1znHze1yjzjiFUnml/cnGZg1LtZf3QGMBrpeXFwCRqRlMjU3m56MZDL5Sh9/I3swc68PgXoP5buJ3rBq7CmuFNT9mvw/AhtiT3aoHeRW32lvxZB9nvssr5ZeiCqwdzQi61Y1LJ/MpL1BxpewK7595n3/8+A+eO/IcF0suMitgFtunb+f7yd8zo/+MDoMyTaEKbZqKPFk66ef+gAemRlxVBfg45uMOVQHKK85gYdHvhoOy9Bo1n2UVMtXBmvqY03z55ZdkFWSRGJBIllEWbw57k0dvmo/zvEFIxkYUrz2POrPKYPsTJ06kj74P/fT90P52Glk/3x4JyqCB+25XmB+DbSx46lIWKzIKqCiqISuxjIDhvVsNygBsbEIxNnb4w2gzoIEnLHi0OwVplRSmG34+r4fZoEGA4Q0AtVX1CH1DtqyzuEo421XqjOtRXK1GCP5nWf6vR7VWj5mR7L86KLtR/B2YtQW1Euob093D5kPEI3DiE4hrmUHpO8qbW8e4oLRwZc/GXH6eNRvPqHVYSPXEDLibuV+s465X38Z/xGgUpobViZiYOOOnm4/tOiN0feTE5c3jl9hn2Ze+hydDniTcpWtPjIYiJiYGU1NTAgJa8iadTS/CUqHGRL2Tfv0W4+PzXMsU/7kfQK/pNu6yrkKSyej94QcoPD3Jfe45NLmGdST27j0DmcyEnJwNHU/2nwrKAshtCEgcnJxI8AngiUo9VYUq7o6ppZePNWPv6XfNL0lihPsINk/ZzCfjFmOsqOanC/Hc+8u9HMs+1u3ySQu8XQmxMufFK9nk1NXTb6w9wkjHp19t4u5dd/PDlR8Idwnni7FfcODuA7wQ8QK+/8feeYdHUe5f/DPbsrvpvZNGGql0pCMtFBGkK4gFQQWvvV87qHivXQTEQrEgCkrvvZd0EgjpkEIaaZtkS3bn98eGkJAEQr33d/U8T54ks++88+5kM3PmW86xC2j3/NX78xHkEuSRNuSnpVKnuTMprva6AphMBiorY7G3uzmZDFEUefVsHlJRxGvvJg4dOkRAeACJIYlk1WXxUf+PmBQ8CQCZkwrnx6OQWiko/TYZbUb5NWY3w8rKipiYGMIyOxCYZ+KIv+G22Gldgp1cxqoofya42vNR9gW+XHcGQRDo1Ldt7SZBkOLsNJjSsr2YTLfGf7I9CO3tjkIpJXH3+RvaX2pnh8Lfv13EzGQ0UVulx0Itu6GIl0QqQWklR1tz44KzcLm2zE4tx+J/1BPzEoyiSK3JhLXsr01N/trv/mrY/y/4sgvELjcXsY/4CPwHwYanIfsAAPUGA+nHD7P+k/fZufFtfMil1tId0X4K9987jflTepJRLbDu7PXfpESjkaJ587HJcadnty0orKJRV27idS8FUwPuvtXvthk0Gg2nT58mOjoa+RX+mjpdEUfST+Nvm0lE+Od4e7VCvEQR4leCZzdwael9eKchtbLCa+FXiPX1nJ/7FKa6umvuo1A44OZ6L4UX2iGdETgUJDI4s5GMWi1jEzI54B1EYFkps49rUVpIGf5YBNJWLjaCIDDUZygjQoNQGyOo1mmYu3su07ZM41jhsVYOdmOQSwS+CvVEb6pnxJE9xGyJ4YTrVpwv+POC9xvsnribTwZ+Qn+v/sgk1yfZYazUUZtQjLqbK749uiGaTOQkxt2ytV8L7XEFqK5OwWisven6sp8zz7O3vJro9CRcFXLGPDCGXyW/kludyxd3f0GMX0yz8TI7C5xnRyJ1UFK6LIW61PaJIEdGRtJLr0Aiwp+u+ew6t+um1n0tKCQSvgztwPNezlicqqSkgxKT9dVr45ydh2E0aigvv3Wf02tBoZQR2seDzNjiq9ZIXg2qztHUJSRck+zWVuoRRRFL2xuPUqkazuHNRM0ao2U2//vRMk29EUSw+gv6YzbF38SsLQSPAFtv2PAPWNwH0nfAhB8Q7QM4/+1stn8+j8Wzp7H+4/fJP5NK1JARdHm2Hz1d5NSq3di3UUPv4nR6Bzjy0dYzlFRf30WkYs0atCkpuLz4Ili7sCCvmnXVjrjKTJw4cc8t8dxsCwkJCZhMphbaZbW12ew9Mp38agf6hXTB1XVU6xPknYSSM//xaFna0UJyU8w3Qgs/Pzz//S90Z85Q+Prr7YpAeHk9iMmkpaBw9dUHquwx+vZnUYmBISfSyKrV8bzCwOhDF9EU1zHs0TCs7K9+Ue3u50hVrcDXA1fx5l1vUlRTxMztM5m5bSYJxTfn75ddmc2nsZ8ye9MYZMWLKcEVH79XeOHRR1BZy7GJ74idhd0Nz685XAAmEeu+nrgFBKKysSUrtn1p41uFa7kCVFSYyYPdDXZk6nQ61u/YyZsZ+TjXVPFiZAjDpgzjlcRXKKktYfHQxfTz6tfqvlJrBS6zI5G7WVL242lqE0uueTxBEAitqaFOpaTa3ZkPj39IraH9Bes3AkEQuLdCiqVOZKePlHvi0snTtk0o7O17I5Wq75h35iVEDvIyN1vsuzGbJnXnzhgrK9Fn57Q5xlhvolZjQGkpvykxZplcioVKRp3GcEN2aAajibJL0TLZ/z5Z0RhNCAJYtpFC/6vgr/3ur4YOveDR7TD5RzDVw6qpVH5xN3+edWF1hj9njh4mICqa8a++w+xFyxn00CzcQ0MIn92NHmqoVbuxeeV5XnOsRmsw8sHm0+0+tLGigpJPPkXVrSs2o0cx/9h8cipzeaDHl9zVa/tNe25eDSaTidjYWHx8fHB2vuxlWFWVxMnYSZwtcwKgb8hVJDriV4BcDWH33dK1XQ8uZFWyc/lpNi9MajRAthowAOdnn6Vq8xbKvv32mnNYW4diZ9fzmtIZmbVaxvo8zzvukxloKbCvRwi9y6xQal3w6qbEK+TaNU3dGoR6E85VMzFoIpvu28RL3V8ivSKd6VumM2fXHE6Xtf8zVK2v5vezvzNt8zTG/DmG5SnLCXUMZVGPiYx3seW4oSMaVQe6j/KjIL2Ccyk3Jtdh0tWjOVaIKtwJmaMKQSLBv3M3chJiMV1DwLQ9OJlzkYra9kUbXur+Et7W3rx28DWq9c2j1OUVx1GrA7BQOF3X8UVRJCUlha+++oqvCiuoVSj5ulsn7ANteHjbw+iMOr4f/v01SwskajnOMyNQ+FhzcdUZak5c3bJL1OvRHzuGtEcPOhWGU1RbxOLExde19htByv4CbJyUzB8aQoFWz8jYsyRVt04IpVILHB0GUFKyE/E21Ea2BRsnFX5RzqQcKMCgv/7PWHsMzWsqdXCT0bLG49koEE0iuhsQxy2p1sFfJFoGUF1vxEoqQXIbxNL/P+FvYnYVVJWVcPysjhXnerKjsCMyzXnGOR7gsbsqeSL4BCNsDuIbHoGkSdhV4W1N4L2h9FCZqFW5EvtHEa861rA2Pp8jme1LY5R88SXGqirc/vlP1meuZ33meh6Pepye7j1v2HOzvcjOzqa8vLxZtKzs4kHi4h9AKlWjsXgaqUQgyruN7kGdBk6thbBxoLx6wfjtgtFgYveK01jZWWDvrmbLkmRKzptv1I6PzcRm5AhKPvnUbAx9DZilM/IpLW2ZSjKKIkvOFzP4RBrpgjULT7/HDzXbMJ6vIWnrBYyWFehs2taza4ogV2usLWScbGissJBaML3TdLbct4WnuzxNfHE8kzZO4rm9z5FVkdXqHCbRxNHCo7xy4BXuXn037xx5B41ew/Ndn2fnxJ18NfgrhvgMYUFwB3xUCuak5uLR0wUbJyVH/shEvIEn+prjFxC1RqybyCr4d+mOtkZDwdn2E8krIYoiC7aeYcLiI/T6YBevrk0m7cLVSwIuuQIU1xY3cwUQRSMVFSevW7+spKSEFStW8Ntvv1Ht4EyKd0emeTphKZzjka2PoJAqWB5jJrztgUQpw+nhcCwC7Slfk071obbrHWtjYzFpNPhOmEi0SzQBtQGsSF1xzQaHm0FZgYaC9ArC+nnS38mG9V0CkQsCY+Mz2FHaejrfyXkIen0xVVVJt21drSFqsBfaGgNnj12d4LYGhb8/EhubNuvM6g1GtBoDKmsFUvnN3yLlFlJkCim1VfrrqhU01JujZfZ/kWiZ3mRCZxL/8mlM+JuYtYn9P/3A0jmPcODnZciVljjf9y7CM0kw8FVsajKRC0bIPQh/PG6uqWoC6wFeeHdyp4cV1KpdkMbriKnL4411p9BfowhUe+YM5atWYT9lCvlucuYfm093t+7MjpzdOObKzk1z9GzqLYmenTx5ErVa3Vj0f6FoA4mJM1EpvenWdTXJhSKh7taoFW3UIaX+CXrNHdcua4qTW3Mov1DLwAdCGD03CguVjI1fJVJVVmc+d/PmYREcTP7zL6DLvvo5c3IajIWFO+fPL2+2PbtWx33xGbyVUUB/e2v29ezEeHkFdcl72Lb0FNaOSty7i+Tm5rTrYiyVCHTxsedkTvPIlVquZmbETLaO38rsyNkcyj/EuPXjeP3g65yvNhdAn68+z8KEhYxYM4LHtj/G/vP7GRMwhp9H/swf9/7BQ+EP4aS6HCmykklZ1MmXIr2BlzLz6TnGn7J8DWdPXJ/Fjmg0oTlYgMLPFoX3Zc9Kn8guSKRSsuJOXNd8l2AyibyzIZVFezOZ0NWLsdGerI3LY/hn+5n6zVG2pVzA2AaJjHKOYlbkLDZkbWBbzjYAqqtTMRo17U5j6nQ6duzYwaJFiygsLCRmxEhORvbCVi5lsDKL2Ttm46hyZOWIlfja+l7Xe5MopDg92AllmCOVG7Ko2tO60K9m714EhQLrPr259957Cb8YjkJUMO/YvNvWCJByoACJTCC0t9kIOtRKxeauQXRUWTAjOZtl+S31w5wcByEIUkpKW/o13k64d7TDyduKxN15130+BIkEVVQUdQmtE7OaCj2CIKC2uTXd5IIgoLZuv+Ds1q1bCQ4OJigokO+++hTnK6Jl586dY9CgQXTu3JnIyEg2b94MmA3QL+lxRUVF8ccffzTu8/nnnxMeHk5YWBifffZZ4/YXX3yRkJAQIiMjGTduHBUVFYDZlmjGjBlEREQQGhraaEkE5q7ziIgIoqOjm3XtT548ufH4vr6+RDdEJsvKyhg0aBBWVlbMnTu31fc8ZswYoiIiAbCWSf+r1tVURPaNN94gMjKS6Ohohg0bRkFB+x68rxd/E7M24BUaTp9J03j0i2+Z+t6/iB4+CrWTBwx8BZ5OgG4PAwKkrIGV48yRogYIEgGHycG42VjT21NBrdqFXhctsU1JZumB1qMd0KBhNm8eUltbrOY8xgv7XkAlU/Fhvw+RSlo+RTSPnqU3RM++v+HoWXV1NWlpaURHRyOTyTh/fjkpKc9iaxNNly6rkMqcSThfQdcOV5HpiFsJjoHmVPB/AGX5GuK25hLUwxWfcEes7JWMfiqKer2JjV8moq0xIFGr8frqKwSZjLy5T2HUtO1tKpHI8PKaTnnFUTSaNEyiyNLzJdx94gxnarR8EdqB5RF+uFrIMQWPZvvZ4ehqDcTMjsA/0BeNRkNpafsEMbv52HO2SENlbcuUh43Chrmd57Jl/Bamh05nW842xvwxhskbJzNy7UiWJC7Bx8aHBf0WsHvSbt646w0inCPaFMSMtlHzmr8Hm0oqOeopxcnbimPrsjAa2p+SqksqxVipw7p/c0NoC7Uar9DwGyJmRpPIy2uSWHY4h8f6+fGvCZF8OD6So68O5uWYEM5drGX2ylj6f7SHJfsyW01zXukKUFFhrnezv4Zx+aW05cKFCzl06BCRkZHMnTuXrA4BnKyqZYJlGq/ufwY/Wz+WxSzDzfLGJCwEmQTH+0NRd3ahalsuFVuym0UrRVGkes9es9q/Wo2TkxPD+g0jtDSU2KJYNmZtvKHjXg0GnZG0I4UEdHZBZX2ZkLhayPmjc0fudrThlbN5vJORj6kJEZLLbbGz63lHZTPATHaiBntTXlhD3un2dbs2hapzNLqMTIxVzWU3DHojuloDKmt5q806NwoLS7PgbF311dOZRqOROXPmsH7DJtbsOsr2DWvIPNtcsmfevHlMmjSJ+Ph4Vq1axZNPPglAeHg4J0+eJCEhga1btzJ79mzq6+s5deoUS5cu5fjx4yQmJrJx40bS09MBs9vEqVOnSEpKIigoqJHo/Pbbb+h0OpKTk4mNjWXJkiXk5OQ0rmHPnj0kJCTQVEv0119/JSEhgYSEBMaPH89995lLWZRKJe+9916bBuJr167FysoKEyJSQUApEf6r1tUUL774IklJSSQkJDB69Gjefffd1v+QN4m/iVkb8O/SnV7jp2Dn2srF18oFRn0Mc0+AjQdk7YFPO8GJ76ChXV9mp8T+vo441koZ0M2eOrULo/V2HPh1O+cvtl6zUbVxE3UnY3F+9hn+nbaYzIpMPuj7AS5qlzbX2TJ6Nr9d0bN6k8iO0kpOVddibLjQxsfHYzKZ6NKlC5mZH3M2/V2cnYYQHb0MudyGMxeqqdUbWxiXN6LkLJw/ajYs/w/UCJhMInt+PINCJaPvpMDG7Y4eVox8IoLK0jo2L0qi3mBE4eWJ52efoc/JoeDFlxBNbRMSzwbpjKM5a7gvPoM3MvLpY2/N3h7BTHJzaCQ/x873JV8fwYBehTh5WeHn5wfQzAXgaujma65FizvX9o3GQenAC91fYNO4TYwPGg/AU52fYvuE7Xwz7BtG+o9EKVO263iPezsz0N6aNzMK8BrhTfVFLaf2t09ORBRFqvfnIXNRoQxuWUPn36UHZXnnqCxuf6rJYDTx9Kp4fovN45khgbw2MrTx3NpbKnhiYAD7XhzI4mld8LJX8cGWMw1pziTOXLh8g73SFaC84hgqlQ8WFq5tHrtp2lKtVvPoo48yduxY9BZK5mUW0Ml4mD+T3iXSKZLvhn+Ho8qx3e+rNQhSAfuJQVj2ckezL4/y1WmIDdF0fVYWhnPnsBo4sHF8nz596KnuiZPBiX+f+DeVumt0Cl8n0k8WodcaCR/g2eI1S5mUZeF+POTpxKLzJcxKyaGuiUuFs/NQamszqKlp+6HzdiCwqysqG8UNSWeoO3cGUaQusXkKtqZChyC5ddGySxAEAZW1HL22/qp1ccePH6djx45YuXgilyuYOnUK69atazFXVQOhrKysxMPDLGuiVquRNWhjarXaxv+d06dP06tXr8bXBwwY0BhNGzZsWOM+vXr1Ii8vr/EYNTU11NfXU1dXh0KhwMamfaUpoiiyevVqpk6dCoClpSV9+/ZFqWx5XdJoNHzyySe8/vrrmESwlkkQBOG/Zl3//Oc/m21veqyampp2O0FcL66vL/5vNIdTIDwVB98MgpI02PQcHP0ahrwNIaNRRzqjPXMR4osZco8XO9eLDKsR+O7LP3n7rfubTWXU1FD8r3+hDAvjcGcVaw6v4bGIx+jt2btdS7kUPbvkGnDs+CgC/F/A23tGc+FXzLn8Oann2FBiDg/byCR0t7Gk/nwJYcGhFJR8RknhL3i4TyI4+D0kDfIJlwhDl7YiZvErQZBC1NT2n8NbiOQ9eRRlVzH0kU4oVVIqN21CYmmJ1YABeAbZM+ShTmz/NoWdP6QyfGY4lj174PrKKxTNn0/pV1/h/I9/tDqvVGbHEavnWVIShoW0ls9CvJnchJABZCWUEHegmjCHo4QYDgP3Y29vj62tLTk5OfToce00WrS3HTKJwImciwwKaZuMA7hauvLPXv+86phrQSIIfBHagUEn0vhnfSX/CLbj5JYcs1bUNTwBdRkVGAprsB8f2Kr9kn/X7uxdsZSsuBN0jrnnmmvRGozM/TmOnaeLeW1kCLP6t66hJpNKiAl3JybcndOFVSw/nMPauHx+OX6eu/wdmdHbl6GdXPGx8eGFbi8w7+i7TJSDl1vra9DpdOzfv58jR46gUCgYOXIk3bp1Q9Lg8DE/swBd2TpKKn6ln2c/Ph74MSrZrfGsFCQCdvcGILWzoGprDsYqPY7TO6HZuxcA6ybETCqVMvbesZxdfpbd8t18Gf/lTf/9m+LUvnwcPCxxD2i9dlQmEfgg0BNfpYJ3Mgu4oMtgWYQ/TgoZzk5DOHv2HUpLd2BpObvV/W8HpHIJEQM8Ob4hm/ILNdi7WbZ7X2VEJEgk1CUkYNWvL0BjqtHSzoLiBR+iO33mlq7XIjgY6YP/oK5Kj9yp9c9Qfn4+np5eXGyoLfPt0IFjx5rLkbz99tsMGzaML7/8kpqaGnbuvJxGPnbsGI888gi5ubmsXLkSmUxGeHg4r7/+OmVlZahUKjZv3tyqcPj333/P5MmTAZgwYQLr1q3D3d2d2tpaPv30UxwczA9gl4iTIAjMnj2bWbNmNZvnwIEDuLq6EhgY2OIYV+KNN97g+eefR6pUIdJ6fdl/cl1qdUuXhddff50VK1Zga2vLnj17rjnXjeDviNnNQq6CGevBxhOUdiCa4Ndp8P1wOHcUuzEBSO2VWKVoiJneEZ3KiQ4ZsPPn5qH/ssWLqC8uRnz2Ud49Po8uLl14MvrJ61pKe6JnWqOJR0/lsKGkglf93FkY2oF7XezJqNKwzyOAr92CGV14Dx8rl7LR4h8cqqijpqG7Lja3HBdrC7zsW7moGA2Q+AsExZh9Ru8wqkrrOLouE59wR7ytLpIz9X4Knn+BvMef4NyDM9CmphLYzZU+EzqSGVfCwd/TEUUR+2kPYHvffZR+vYiq7S1NmXPrdExIyOSL6q4Ei6n86BnHFHfHZqSsoqiWXctScfGxpt9AI+QehtqLCIKAr68v2dnZmK4SkbsElUJKmKdtYwPAnYCLhZwvQjtwukZLQlcbtBoD8TuubXBevT8PibUcdefWCaS9mwf2Hl7tSmfW6ut5dPkJdp4u5r2x4W2SsisR6m7TmOZ8ZYQ5zfn4j+Y05+J9mQz1upfRXl2QiHXoFD7N9m0rbdmjR49GUna8QsOfpxehrviVEb4j+HzQ57eMlF2CIAjYDPSpUulKAAAgAElEQVTGfnIwutwqihcnUrVjNxYhIcg9mgu8enh4MKrbKPwr/VmdtpqU0pRbsobi3CpKzlUT3t/zqhEAQRB4vIMLS8N8OaWpY3TcWbJqdSiVHlhbh9/xdCZAWD9PJDKBpD3XJ50htbLEIiiosQFAFEV0tfVIJEKzVO4thURAaSlHW2vA2IYvriiK1DVoeV3qxLzyb/LLL7/w0EMPkZeXx+bNm5k+fXrj9aVnz56kpKRw4sQJPvjgA7RaLaGhobz88ssMHTqUmJgYoqKiGqNRlzB//nxkMhkPPGC2rTt+/DhSqZSCggKys7P5+OOPycoyR0QPHTpEXFwcW7ZsYeHChey/oonql19+aYxKXQ0JCQlkZGQwbty4xnvMlcKy/+l1tYb58+dz/vx5HnjgAb76qnXdxJvF3xGzWwErF3hgNXw3zCwTMeIjOPAJfD8cSchoHIc/T/GvNdgW1DP84UC2/gDntpRQ4HUcj/490GVlU7Z8BVZjx/Dsxe9QSBUs6L/guoU+L6Gt6Jmjx3QePpXL/nINC4K8mOFpLggf7+bAqvgd6NWrKbBy4ILdw6QaO/BpbhGm3CJkAkRZq8nNLCXIzZrKeiN28ivWdnYb1JT8R7TLRFFk709nkBp1RJVtImfiz0htbfFY8CGm2lpKPv+C7PETsB1/H+FPP43mojeJu89jZa+k89AOuL39FrrMDApeeRWFjy/K4CBMosiKgjLezSxACnwS4k1QwUfoLpzH5De9MYpo0BvZ+k0yEqmEmNkRSOskcPjfcHYrRN+Pn58fiYmJFBcX49YOW51uPvb8eDQXfb0JxR1Svx7saMNsL2eW5JWwINyehJ3nCB/g2aZUgL5Agy69ApvhvghXWaN/l+4kbN2AXlvXpuNFldbAIz+cIO5cOR9PjGJ81yam2dUX4M8nIXw8dG7b59TeUsHjAwKY2dePnaeLWXY4mw+3nOGznWcZGDCSPPssfjy9hW98H0UulVNSUsKWLVvIysrCzc2NiRMn4u3t3WxOXX09c/a9ibpqB+MCJ/JWr9dbrfO8VbDs7ILUWk7JtyfQJsZj98DDrY4bOHAgiacTKTAV8O6Rd/l51M83va5T+/KRKSQE9WxfzdxoFzvcLOQ8mJzF6LizLAv3w9lpKFnZn6HTFWNhcfVo762E2kZBUA83zhwppOcYf5SW7TOMB3OdWdX6DYhGI3lnKzEaTKhtLZBIBNwaTKtvNeoNRuo0euqqDVi1YvPk6ubBuXPnsbeUo5BJycvLa0xVXsJ3333H1q1bAbjrrrvQarWUlpbi4nL5vIeGhmJpacmpU6fo1q0bjz76aKPn8WuvvYaX1+X/s+XLl7Nx40Z27drVSAJ//vlnYmJikMvluLi40KdPH06ePIm/v3/jelxcXBg3bhzHjx+nf//+5vdXX8/atWuJjY295rk4cuQIsbGx+Pr6ojPUU1pSzLC772ZvQ8T4v2Fd9fX1FBcXM3DgwMZ1XcL999/PqFGjeOedllaNN4u/I2a3Cq6dYOIyKE6FrL3m+rO7/wlZ+1D8OQSXDsvQxp/BTWVFyGh3tEoHtn6bSenhOIrefx+JhQWrBslIK09jft/5N1xYfAlXRs8SMz7hnsNbOViu4YvQDo2kDKC0NBO1+ms8LLN4qNMUPusylO3dgznTL4KfIv150tsFk9aIplrPMYmB0IOnuPv4GV47m8e64nKKdAZzGtPKDToOvbnzeANIO3qB2gP76R3/PppfVmJ3330EbN6E7b33Yj91KgHbtuIwYwaVf64jc3gMIeV7CIi04/CaDNJPFCFRKPD64kuklpbkzZ1LTlEJkxIyeeVsHj1sLNnbI4T73R3p0GEGWl0BpWVm6QxRFNn3UxplBTUMfaQT1g5K8Ohijp6eNhdoX/LNbFqgejV097VHV2/iVMGtrSG6Fl4LcCfCSsUiPzDWi5zcnNPmWM2BfASFBKtr3MgDunTHWF9PbnLrelEXa/Tcv/QoiXkVLLy/S3NSZtDCqvshcxesexL+nHPZIq0NmNOcbqyadRdbnu7HuM6e7E5X89aRV9kfN5hn1v/A1m3bWbRoEfn5+YwcOZJZs2a1IGUGo4GpO55DW7GDQQHTeOeuN24rKbsEZUd7LMOqQBTRX3Bv1cJJLpczYcwEwkvDSb2Yyu9nf7+pY+pqDaSfKCKohxsW10hfN0U3W0s2dw3CTiZjYmImxyWDALFVWZnbjai7vajXm0g9dH0dcuroaEw1NWgzMjj6ZyaCREBl1X5idyOQyaUoVDK01fpW5Wl8QiPJzc6kprQAvV7PqlWrGDNmTLMxHTp0YNcu83k+ffo0Wq0WZ2dnsrOzqa83d33m5uaSlpbWeP0pLi4GzB2da9eubYwcbd26lQULFrB+/fpmabsOHTqwe/duRFGkpqaGo0ePEhISQk1NDdXVZtmampoatm/f3qxrcefOnYSEhDQjfm3hiSeeoKCggKzsbH7YtgP/wMBG8vPfsK6cnBwOHjxIUFBQ47ouNU0ArF+/npCQkGvOdyP4m5jdSgQOgZgFkLYZ9i2A/i+aOzi7z0Re/CfuylnU//Em/Xt4cLGTAq2FPRsWp3HxeBKlDwxhxYX1PBT2EP29+t+yJVlYuOAdspDPVN+RZnTnKT6nl/7Pxs7N2tpsEpPuR6mqpmPAZ7i5Xb4I2MikDHa04bUAD562NSvDv989gBf93HBSyFh14SKzU3KJOpxCb9tpPNv5I34triK3Tndbvf2aoir9PKWvPEfUqcVYONjg89OPuL/3LlK7y0r2UltbXF95Gf8N61H36kXJp58SsOYlgqVp7FyWQn5aOXJXFzy/+IK1/qHcnZhNQnUt/w725pcofzyV5tSGk+NglBYejdIZKQcKSDt2gR6j/egQ1lAMLggQMspMKPQ12NnZYW9v3+4GgK4+5nqJK2UzbjcsJBIWh/lQbC3lfIglqQcKqChuSYTqK3TUJpZg2d0NifrqNzGP4E5YqC3Jim2Zziyu0jLlmyOkF2n4Zno3RkS4X35RFM3WZ/mxMHE59H8JEn6Cb4dAaXqLuVpDqLsN74+L4NO7/83DXTJR1nux6Zgnz+/RUOIUzYMzH2+WtryEuvo6Zu96ivTiPbh5zODzPi/dtgLf1lAXfxipvQMK/2BKv0+hJq6lhImvry/jQsbhXOfMZ7GfUVbXPn3E1nDm6AXqDSbC+7cs+r8WfFUWbOwaSLS1mqezDGyRPURxyZ2VzQBw8rLGM9iO5D15mNpIEbYGVefOAOStP0BxbjUWalmr9ZK3GmobBSaTiPaK7mt9vYkqnYn3//UJ94waSWhoKJMmTSIsLIw333yT9evXA/Dxxx+zdOlSoqKimDp1KsuWLUMQBA4ePEhUVBTR0dGMGzeOr7/+GienhqzI+PF06tSJe+65h4ULF2Jvb64Tnjt3LtXV1QwdOpTo6Ggef/xxAObMmYNGoyE8PJzu3bvz8MMPExkZSVFREX379iUqKooePXowatQoYmIu25CtWrWq1XShr68vzz33HMuWLcPLy4vU1NTG12qNJkwiSLl87v8b1tUaXnnlFcLDw4mMjGT79u18/vnnVx1/oxDu1A30VqNbt25i05bY/ypsfhGOfwP3fA5dHzJvu5iFacvbSNLXYZLYUTfwZWb+4Ux/jRVKXTn7gpdi6OzBsphlyCW37qmtRG9gckImGbU6FgXb41Uyj9LSXdjadqWD9yOcSXuDurpaLpZNY+rUV9ucZ/6mVJYfziX5nWGNYocGk0iyppaj8Zs5VlzEMde+VDQ0HLlbyOlla0kvOyt62lkSpFbeUjVn0Wik/KefKPzXp4hGI7aPzsLrqVkIimvXh9QcPkzRBx+iS09H4xxEeuAEIt4czXsVZewv19D1dDLzdeVEP9uyGSA3dwkZmR/h7/YHW78uwyvYgdFzIptf0LP2wop7za4Rofewfv16UlJSePnll1sQgdYw8F97CHK15psHWxbo3m6sKizj9fhcnt1SSWCUM8Nnhjd7vWJTFppD+bi92B2Z/bW7Pzd8toD806eYvWg5QsN7zyuvZdq3xyiu1vHtjG70DrhCjf/Q57DjTRj0Ogx4ybwtYyesnQX1OhjzhTm9eQ1oNGc5dnwE5RfHkJRsS4ZURRIOaGo9UMoljI32ZEZvX0LdzZ1W1fpq5u6aS1xxPFrHR9g5+Al8VHdOcV00GDjbuw/WQ4fi9uY7lK1MRZdZic1wH6wHejcjiFqtlveXvM8623WMChjF+/3ev/7jiSK/vHMMuVLGxFdu/LOmNZp45sw5/iyuYDA7+a7vbJRy62vveAuRnVjC5kXJDH8snI5d25dKFUWR9D59KbYJJbfnTDpPtmnUb7ydEEWR8sJaREQc3C0b/6755XVcrNET7GaF4i8gKHsJF3R6inT1hFmpkN0BYnyncPr0aUJDm4tPC4IQK4riNf/Z/o6Y3Q4M/8Cc0tv0vPkmDeDgj+SBFdT1X4Pe4I3l7ldZbPcqBapYtBb29Dv7GG9bzbylpKxQp+e++Ayy63SsjPRnlHuHZrpnyafmYDLJSIgfRlTUvVedK+5cBRFets0UqOUSgS7Wap5MfJ/lms2k9otiT/dgPgjyooetJYcrNLx8No+Bx9MIP3SKh5KzWHyumISqWupvQGX+EuqST5EzcRJF739AubU/ulcX4/383HaRMgDL3r3x+2Mtbm+/jY2hmOjDH7Dr7VfJOpfPR0FefFuag8WSRVRu2NBiXw+PyZgMjuz6IQ9LWwuGPtKp5VO2Tx9zI0hDOtPPzw+dTkdhYWG71tfVx4HY3PI7FnVsisluDgz1ceBQoAUZJ4spzr0sQ2HS1lNz/AKqCOd2kTIwpzNrKsopys4EILu0hkmLj1BWo+fHmT1bkrKz22DHW9BprDnifAkdh8DsA+AaBr8/ApteMJO0NqDT6Thy1BzZPHdOyehRI3lp9nBkvgsZ2S+ecZ09+TMhnxGfH2DKN0f4PT6VR7Y+QmJJEpVOc3gyfModJWUAtbFxmKqrsRo0sNElQB3tbNY6+zMD0Xj586BUKpk2YhqBlYFsyNrQqj/otVCQXkH5hVrC+3tce/BVoJRK+LqTD7NcjexiCA8kpJjNqO8gfCKcsHFWkbir/dIZgiBg9AlFVZROzzH+dywyKggCKhs5RoMJvdZ8nvT1Ji7W6htry/5KqK43oZZK/qdI2c3ihomZIAjBgiAkNPmqEgThGUEQ3hYEIb/J9pFN9nlVEIQMQRDSBEEY3mR7TMO2DEEQXrnZN/Ufh1QGE743C62uftCs79UA5aDB1IQupdTwFhbVtbzn8C86WS5Br7Dn4PfFlJ04dUuWcK5Ox9i4DAp1Bn6JCmCAg/kJtmntmZ/fM1wonIFU6klwcHCbc+nqjSTnVdK1Nf2y3ENwMQs6T0ciCIRaqXjY04klYb4k9A7jaK9QPg3xZpijLWdqtLydWUBM7FmCDyYzJSGTz3IucKRCg7YdKQijRsOF+e+TM3kyhuJi0rvNIi/mRaKnNhGzFUUoPmOOuiwfA3s/bHUuQSajduw4Pvh0Cb8OGcXgEwf54bWnGbbmV1yefQZ19+4U/vMN6k4173yTSm0pjX0RfY2UIY/4tF5sLJVD8Ag4uwWMhhuqMyur0ZNdWtOu8bcSgiDwUbA3uVE2aC0EDqy9bAFUc6wQUdfcfula8I3uCoJAVtwJ0i5UM3HxEbT1Jn55rFdL2ZWSNPj9UXCLgLGLWmrh2XrCQ5vgrrlwYqm587k8p9mQpt2WZaVHMJlseeyx1+jRowfRrtHMipzFgdJfGdilkKOvDubVESHkVuTz1ok5nLmYST1P4GHdhyc73LkC9kvQ7NmDIJdj1dsskSPIJNhPDsZ6oDc1xy5QtjIVUxMNrKCgIMZ7jkddr+adQ+9gMF2fF2PK/nws1DI6drv5LmqJIPBOaDSzJCs4olEwNj6DQl37PE5vBSQSgchBXlzIqqQou+raO2CWx8ird0ddV4yPz50lQ0q1HIlUoK7KfI5KqrUAuFj/NTwxL8EoitSaTFjdoUan/y+44bMhimKaKIrRoihGA12BWuCSB8Snl14TRXEzgCAInYApQBgQA3wtCIJUMItsLQRGAJ2AqQ1j/39DaQP3/wpSBfw8CWrMdSCCIGA/LhCtoRNFui/4UNGRINsERlm9h05uzfqFKZSdvLk2+KxaHePiM6ioN7I6OoBeds3VizPKM/hX/Dc8cnwNiytXkeOXw47zOyjQFLQapTmVX4XeaGpdvyxuJVjYQKeWETdBEPBVWTDV3ZHPQjtwtFcnEnqHsbiTDxPdHCjSG/gw+wLj4jMIOpDM2Lh0PsgqZE9ZVbMnblEUqdq+nayRoyj/8Ufsp0ym8OHPyLOOYtCDnZCKekjfYY6ifB4JX/c0p8JK02HvB3Dk62brEkWRnwvKGHj8DPsN4Pvqy1h9+RPl9iGUf/0VWWPuxeae0Ugc7MmbO5f6Jsr9JzZmc/GcI65dfsYgu4oCe8go0FZC7iGsra1xcnK6DqFZ83k+mXPnZDOawkYm5ctoPw50UnEhrYJzqWWI9SaqDxVg0dEOhafVtSdpgNrGFo/AEA7EnmHyN0eQSmD17F6Ee16hl1V7EX6eDHIlTP0FFC31gwAz6R0+H6b8DGVZsKQ/nDFb0pSUlLBy5coGkVgVbu5VuLsPwNr6clqtqSuATixnWLQEK78lqNV1qGvmokn1pGz7ed764xSnC9t3g78VEEWR6r17UPfsicTysh6XIAjYxvhiN7Yj2rSLlHyThLH6MuEZM2IMPTQ9yNHk8GPKj+0+Xm2Vnsz4EoJ7uSFX3BpSIghSprgoeFnyKdl1OkbFppOqqbslc7cHob3dUSil7RacPX2ogCKpufFDm3RnvT6FBlkOvbaeOm09F2sN2Kv/etEyTYM0iPXf/pjNcKto6mAgUxTF3KuMuRdYJYqiThTFbCAD6NHwlSGKYpYoinpgVcPY//+w9zHfQKoKzNpmDamXuvjj1B5aiKB2JlA1i++7rOEXywhibP9tJmdfJVN24MANHfJMTR1j49PRmkTWdu5IFxvzRd5gMrA1ZysPb32YcevH8Uf6H3gJ5sjHkdojvLjvRYavGc6g1YN4avdTfJv8LccKj1FjqCGuQVeri49d84NpKyF1nbnep60b6RVws5Az1tWeD4O82NMjhNN9w1ke4cejXk7oTCJfnStialIWQQeSGXYyjQWH4oh79DHy//E0UgcHfFf9gnHKU+TEZjKs8zFcDz8GC3zhpwkQ/yO4dIJRn8Azp+DZUxB6D2x7DVLMzwwFWj33J2XxXNp5IqzV7OkezMOeTvjdHYXrvz8jLuppausVXHjzLWS2dtRfvEje088g6vXkJJdycrNZgNWvSz15eT9iMrXhfRcwGGSqZunM3NxcjMZrp3j8naywU8s5mXtnGwCaoqutJXcP8aFCLWHzb2epSSjGVKXHut/1F4nrA3vynSkaS7mE32b3pqPLFfVHRgP89hBU5cPkn8C2HRG5kFEwex/Y+8GqqeQsfZAlX3/V2G05bdpQjMbyFsblTV0Bnt37LDO2zkBv0vPh3Uu5EN6VvqMDmNDFqzHNOXnJEbaeKqT+OorKbwT67BwMueewGjSw1deternjOL0T9UW1FC9KxFBibsywtLRk1t2zcK9xZ2H8Qi7UtM9p4fThAkxGkbAb+HteDc7OQwk3HmZFgAYRGBOXzrbSSop1BsoN9dTUG9GbTLclTa9Qygjt40FmbDGa8rbT3GCWuTmxOQfL6AiQydo0NL+dUFnJQRCovHgpWta+8oD/JWiMJgQB1NK/I2ZNcat0zKYAvzT5fa4gCA8CJ4HnRVEsBzyBo03G5DVsAzh/xfZWTe0EQZgFzAJz2+zthCiKaGsMqKxuUmzQuweM/RrWPAobnkYc9QWF8+ZTSh4nnXdzX9EQ+g/wZHTKROKddCzwPcaWxB6s+zafsWmv4TDtZVC2rsZ9JZKqa5mSmIlCkPB75wCCLJUU1RTxe/rvrDm7hpK6EjytPHm267OM8hnFj9/8SIxrDJPvn8zZ8rMklySTXJpMUkkSe8/vBUBAQIUnjr5e7C+sI8IQQUe7jmb5gOTfob7uprTL7OUyhjvZMtzJ/B5r6o3EVtVytLQC2aqfGfT7L4jA4vumYuzdkfvOLCfk7G5muGRDAWDnYz5+4DDw7WsW/G2K+5bCirGIa2exW6vkiVpPDCaYH+jJw55OzRoSgnu6UfPICA6u7UhP+zSkB34BvZ662FjSX5vPftNgnLyt6D8liPLKGSQlP0Fp6S5cXIbTAgo1dBwMZzbBiI/w8/PjxIkTFBQUtJBnuBISiUA3H/v/WMTsEub4u/GPnsXY7Slj//ZsurqpsQi6ik9qKziYXsoHZ9Wo68uZF2VJB8dWCPy21yF7H9z7NXS4up9lU4j2vpy+61P0G14kOn8dj1sGoZr2M5bugeTnmy9HdnYt5/Ox8WFS0CSWpy7HRmHDTyN/4pVsIwqhho+7B+BqIeflmGB+PXGeFUdyefzHODztVEzr5cOU7t7YW956AVJNg4J4U7X/K6Hq5IjzrEhKl6VQsigRxxlhWPjYEB4eztiksXyj/4Z5h+bx1bCri16aTCIpBwrwDLLDwb39avntgYN9HyQSFY6abWzq8jrTkrKYkdx6pFguCMglAoorvssFAQuJBLkgoGj4XS65/LOitdcaflcEKpHtFvlx41lUd7u3Mr8EhSCQfbKIdKmRIfcEwolgLsbGUT8iBoPJhICAIIBAw9dtqj2TSCUo1DJ0NQYcrOV3TLfwvwnV9UaspJJb2hj2v4CbJmaCICiAMcCllr5FwHuA2PD9Y+ARoLUzL9J61K7VxylRFL8BvgFzV+ZNLfwaOLwmg6zEUia+0u26RAtbRcQEKMuEve9zMa4OQ1YW30yQcP+4Psi3WqNfn83rMUH8489kdt/zEKOC8tj0m8CfByMZm343DuNmQrdHQNZ2/cHJyhruT8rERiblt6gASiqTeO7EKnaf241JNNHHsw9vh7xNV4euxMXGsXzzcmpraxkzZgxyiZwwxzDCHMOYwhQAKnWVnCo9RWJJIkuO7kWiSuadI2ZerZapCXMKIyIvmUj3ICLtvHG+uTPUCEuZlO7nMvF66210aWmouwah6qtiQfm3KE9WYhCkHLeJYKnjE6S498fVsxN32VnT084Sf5lFyw+ZXEXR+JXUfzeMrltmMrzvdzzfcxC+bRR2dx7WAc1FLcf2Sej72re4n9lE8fcrOF7oh8m6luHPRiBTSHFyGoxS6cn5vOWtEzMwR3XObITCeHx8zHo32dnZ1yRmYG4A2Hm6mDKNDker/0zdiVQQeH1MCEvjjlJdqqP7ZN/rukntTC3iyZ/i8He2YljGeqpSvWDkFecqdhkcX2KuG7uKiOyVaC4SOxGv4Ik4HX4XVg6H8d9Srj2OQuGEWu3XYt/9eftZlbYKtUxNnaGO7Re17C3XMi/QE1cL8/+6nVrB7AEBzOznz87TRSw/nMOCrWbR2kvdnJ082ufR1x5o9uzBIigIuefVI1gKb2tcnoyi9IcUSpYm4zglGFW4Ew+MfoBDKw6xr3AfB/IO0M+rX5tznE+9SHWZlrvGtc9h4XoglSpxdOxHaelOgoPeZn2XQLaWVlJjNGEQRfQmEYNJRC+aGr6bf298TRTRmZqPNYgiNYYm20RT41j9FXMATPSQ0+FEKfPc6qmXtfF5lQNDbfm+uJA5Lt6MPribUp0ek0bbcmwDSZNgJmmNhA1zGaQEATcLOdY3kIasEUTkgLXw1yNlepMJnUnE4Uqx8r9xSyJmI4A4URSLAC59BxAEYSlwqRAnD2h6R/LCHPPgKtv/Y/CPdiZpTx47vk9l1JxIJDfbMTLgJQzZqVz45BgJARI6jprCsIBh1E+uo+iLOHolltM/0ImPt59l5PMDGKnKZvOKbP4seol7V72B49FFMPhNCLsPrpBcOFRezfTkbFykeh60Os0z218jqzILWwtbpneazqSgSTjKHDl69ChfHv8SrVZLQEAA/fv3x8fHp9Xl2lrY0sezDx1UnflolQ/vjunEgHAJSSVJJJcmk1xwnBXSOvOF7/fBuFm6EekUSaRzJBFOEYQ6hl63fY2xspLi99+kYv12ZJZSPPuWY+25F6HaCUJHUenQn19XWyMJ8sOjrwvnKjXsvqjhtyKz56ezQkYvW7M8x112VoRYKllTVM4b6UU4hy9gW+Jcvoh7DqHLTlC13okmCAJ9JwdRU6nn4MYCYh6bTqGqP5qkaiKTF1E8ZR7Cq69iM2okXp7TyMhcQLXmDNZWrQgNBsWYvUNPb8RySFdcXV3Jzs5uVKO+GrpfqjPLLWd42M2JDd8MPFQWBHipqUyp5tvcMl7t6X7tnYANiQU8+2sCYZ62LH+4Oyd/PkXq/t3U6/XILnXP5hwydy4HDIYh7VPPbuptKZfLm3tbht8Nv81AXHkfNv5OiJ2HtyCSW7K38NqB1whyCGJ+n/k8tONJ5mWVEG7jzMOeTi2OJ5UIDA9zY3iYG2kXqll2OIc/4vP49eR5evo58FCDN6fsJlIxxooKauPjcZw5s13jZY4qnJ+Iomx5CmU/ncZ2tD+2fTyZ23MuzyU+x9sH3mbzpM1YSFsn9Kf256OyluMffasep5rD2WkoJSXbqa5OxsYmkgluLU3ubwdE0UzOzruXs/WzRH6XOeJ1l1sjAdSbzGQw4WA+qccu0HtqEGonFYqiPij3bMUB8FTKETH3EImAiNjkZ/OXSRQv/y5CnclEbp2eYEsl8uu4T+jrjVzUGnCWSdDXGBBtLRAkAlu3buXpp5/GaDQyc+ZMXnmleT/cuXPnmDFjBhUVFRiNRj788ENGjhxJTk4OoaGhjY1cvXr1YvHixbfk3N4OaOrN5QE3Qmj/13EriNlUmqQxBUFwF0Xxki7AOOBSm+F64GdBED4BPIBA4DjmB49AQRD8gHzMadHmDt//Abh3tJ+BZn4AACAASURBVKPf5CD2/ZzGiY3Z9Bzjf3MTCgLnkm0wmgT2DzDxhccQAGROKuzGBFD+ezov93dnXPZF3tuYylf3d2GUILJ5eQ7rKudzb9V3OK55FA5/CUPfBf8BAOwuq2Jm3H7sa3dj1BxkUX0dYY5hvNfnPWJ8YzDUGThy5AgnTpzAYDAQEhJCv3798LzGk/klNBqX+zjgY2OLj40P9wTcA1teRnfqEKcfWkNydW4jYduea/ablApSguyDGolapHMkPjY+SK58MtTXIGbupfr3FVxYm4RRK2IfWIPzUF+k4fdD4HDw6IxJhG0LYpFZ6rh/TBBKSzmPeTsjiiIZtTqOVmo4VlHDkQpNozm7SiKhzmSih60ln3UdiGXkGvhhJPw4AR7Z0maKWCIRGPpIJ9Z9lsC2b1MQTSJd7nbD8XQxxtIKCl54gfKVK3F86SkkEiV555cTGvpBy4nUDuDbxxw1G/IWfn5+nDx5kvr6+hZedVci3NMWhVRC7H+YmOnzNQzIq2O1swLJoRK29y1nmMfV05mrT5zn5bVJdPd14LsZ3bBWyvHv2p3EHZvJS002d2qW58Lq6eYasQnfmzuZrwJRFElNTWXbtm1UVVURHR3NkCFDsLJq0ojgHAQzd2FcP5sOp9aj1Z4EvxKwMhOQ1WmrmXd0Hl1du/Ll3V9ipbAiqOO7ZFQo6CweRCpcXcU72M2aD+6L4OWYYFafPM/yw7k88VMcHrZKpt/le8NpTs2Bg2A0Yt1GfVlrkFrKcZoZwcVVaVRuyMJYoaNnTE9iUmP4Xf87i04u4pmez7TYr/qiltzkUjoP90F6m1JnTk6DEAQpJSU7sLGJvC3HaA2CYE5X+gc74ORtRdb+Qnpeof9WW6XnxPZChoY7MjzU/H9lGNCHDEBZb8BJcf3ZkTqjifRaLfk6fZuR+NZQXG2ug7Oxs0BTqkVba0ChkjJnzhx27NiBl5cX3bt3Z8yYMc301ebNm8ekSZN44oknSE1NbSRlAAEBASQktO608d+GaqMRmSCg/FsmowVuipgJgqAGhgKzm2z+SBCEaMwPFDmXXhNFMUUQhNVAKlAPzBEb5OcFQZgLbAOkwPeiKN4ad96bRFg/D4pzqji5OQdnb2v8O9/4E2Z17En0m3eyrbeCV5UmLFY/CI/tBjtv1F1d0aaVw6ELPN7Vmy+O5zK5ewn9+nZipCiyeUUu63JmMnb0OBxyv4QVYzAEDGah30CW5O3HUpeGKFEw3G8EU0KmEO4UTkVFBbu27SIuLg6TyUR4eDh9+/bF1fX6WuNjc8tRK6SEuDUp2K7XQdKvWISMJtq7P9FNxpfWlXKq9BRJJUkklSaxMWsjv6b9CoC1wtpM0qy8iaitITI/FfWpY1w4rqLmghKlhxrvJyejGv4gWDcnIwnbcik5V83wx8KbpZYFQSDQUkmgpZLpHuaIx3mtnmMVGo5X1hBiqWSGpxNSQQB1JExeAT9NNDdjPLAGZK3fSGUKKT3v9Wfdp/EIEoHAPh2w7vId2RMnIXVwQJ+XR94DM3Eb4E3x8D/p2PEl5PJWCEvIaNjyEpScxdfXl6NHj5KXl9coodEWlHIpkV62d9wB4EpU789DopQxfnIQm75I4sc/zxL1aJfGlN+VWHYom7c3pNI/yJkl07qiauj48w6LRKawIDPuBL6hwWa7JWM9TF0FKrtW57qEK70tJ0yY0HaNqUJNce97qdDvJjQrGxb3hYk/8G1VKp/Hfc4ArwH8e8C/UcqUpGjq2FalpJM0m22nv2BShyi6u3W/5jmxUyuY1T+AR/v6s+t0EctuMs2p2bsXqYMDyoiIdu8DIFFIcZwWSsWGTDQH8jFW6pg7Yg7H1xxn2ZlljAsZh49t84h46sECRCCs781pl10Ncrk9drbdKSndQUDA87ftOG1BEASiBnuza9lp8k6X493pcsQubmsuRr2RHvdcTnHL3d2Rubmh1V+f3MglqKQSXBVyLugMVMjqW/oItwJ9vZHyGgMOlnJUajl1cj11VQbik07SsWNH/P3NgYApU6awbt26ZsRMEASqqswdw5WVlS28NP8/QBRFNEazTMaddNb4/4KbImaiKNYCjldsa7MSXBTF+cD8VrZvBjbfzFpuBwRBoP/UIMryNexclsoEt243VCwrGo2kvv4sBmsIe/4tfJ07wXdD4Zcp8MhWhP9j77yjo6rXr/+Zmkky6b1CGgkkJEBC7yggvShNpAiiYLtXxY6IWEBQsCuCgCKIFAWU0Iv0QKiBhCSQ3nsmmUyf8/4xISEmgVD03t993WtlzcrMd86ZnMyc2Wc/+9mPlR1OY4LRZ6p4OE3Ddmcb5m+/wq5/9cavdzhDzQKxP2ay7XdXej+xgj0lK9hScpbS66l4CHImtn2ciVEzcFQ4Ulpayvbt27l48SIAUVFR9OrVCxcXl9u8yqZxLqucDn6ODUs1V38HTXmTpn9Xa1f6+fWjn18/AExmE+llKSSkbOdSzjEuZZ/kW/FxRGYYGSfwyHEnkIgpmDEAr6lPIHVrZ4lEuAkVhTWc/j2dgChXgjrdnhz7KeT4eTo3XUIJGgCjvoRfn7LMYBzzbaPSMIBWbeDQuqS68Sk7v7zII6/E4PPRUnKeeRb7oUOR+fpQunYtricEMhJfIOjFrxDb/MncHjbMQsyu/k6rmDmIRCLS09NvS8wAols7sfpYOlqDCYXs75f7jWVaNAnFKHv54NjOFbf2znRMLOPFc2ms69amkWH3y0PXWLonmcHhHnw2qWPDMGK5Ff7to0g/fxrB5giiokSYvAVcg5vdv9ls5tChQxw/frxx2fIWqKiIo8TPGwasRtg0leXbH2WNgx3DAobybq/3kIllmAWBV5OzcZRKWR/9IE+UruLNY2+ydeRW7OQtS62XiEUMCvdkUG2Z8/uTGfxyzlLm7BLgzOMtKHMKBgPVR49i98ADiO4iMkAkFuE4Mgipk4LK2HTkKj1z2szmrez5vHnwTdaNXlf3xWcyWeZJtgp3wd71zmwGdwo3t4GkpL5LTU16kz6/vxoh0R6c+OU6Fw9m1xGzqjItCUdyCOvuhZNnw/O4dccOaAz1MSRHN6VQkl19R/vUmM0kCAI2EjGiJizVrn5Keo9vA9SqZSJws1MgEomwsZdTVaolKyO7gQfV19eXuLi4BttZsGABgwYN4vPPP0etVrN/f/0YrPT0dDp27Ii9vT3vvfcevXs37zX8T0JrFjCaBZT3Karlfw3//zkO7xBSmYSHnmqPVC5m1zcJ6DTNxCPcAmdXfoh9RgnJj3ZnaPhYcA+rHXieZAnUNJsQ28hwmhCKpFTLa+5OpJeoWfFHGgC+fcIJGa5DL1ZweGUue5IzKLaJZIo4ggPZ2czeuxjZ7nfZ/vP3fPHFFyQkJBATE8Pzzz/PqFGj7pqUqXVGkvKrGgfLnlsHDv4Q0K/5J1cXwfkfkWyeTvC3AxmzdxFvJ8exVRrIIUbw408uTPrDTHaEO+8868ZLHod5dM9jdNvQjcmxk/nw9IfsSt9FtiqbQ+uTkEjF9J0U2uKrK2OFjtL1SVTuTm88LDhqIjzwNiRshv1vN3quYBbYvzaR6nIdQ+a0Z+TzHdCpjfz2xUWsevTF9blnUcXGInF2Jih2F+ZoZ4w/xnF9yBAqd+xAMN8UreDgC14d4OrvWFtb4+Xl1fKg2VbOGEwCl3L+3oHmN1B9PBcQoexhKXsPfDgEuQkkJ0r4Oru4bp0gCCzdc5Wle5IZ3cGbLx/t1ICU3UBQpy6Em08juroTBr1v6Vq9BY4fP87Ro0eJiIjgueeea3K2ZVMorziNo2NnzO7teKfjUNY42DFRVcUH2enItJZBxz/llxGvquHtYG+8rO34oPcHFNUUsSiuiZJ0CxDqaccHY9oT9/qDvDm0LXkVGuasP0efJYf46vA1ytRNh63WnDuPWaVCeYtuzNtBJBJh18cX50mh6LOr6HTRg+6GblxUXWRn6s66dRkXS6ip1N/VXMw7havrQACKS/7+2ZkAEpmYiD4+ZF4upbzAEtQcv9PSHdp5eGOiaNOhA5hMmA13p5oBWNWW5HS3mWpSp5bZyOs6MRU2MsRiUaP5mdC4K/Snn35i+vTp5OTkEBsby5QpUzCbzXh5eZGVlcX58+dZtmwZjz76aJ2y9t+G6trYILv/DztRW4J/2iFaADtnBQ89GcH25RfYvyaRobPbt3jYbUFeKsKKH0kLtGbSsze1sQc/AEOXWMzPe+fBQ4tQBDmi7ONL+z9yGNLKhS+PJCB2OMa+3F9Jr0ynW1Ao0denMyLxeS6HePLsuB4Up8ajiX2L1hdWMQgFYa3G4z16PnZO927svZhTgcks0OlmYlaRZRkz1e+1hkqT2Qz55yFlL6TugbzaXCA7L4gYCyGDMLl0pOjzb6jYvAUrby88v/6Ktv37MwwoUBfURXVcKr7ElpQt/JhkCcxU2CsJ7xGOkHWV9jXtiXCNaFbVEASBmvhCKn5PQzCYwSxgqtTj9EgIopuVi14vWHKzTnxmIU9d66vxZ3dnkJlQSp+JbfAMsPjQHnoygp1fXmLXigSGPf0UuqtXKVqyFEWbNngufYerv87BY6ecvFdepezH9Xi8/ho2tUOSaTscDr4Hqry6cqZer0d+mxFSNwjxmYwyugT8PQbqGzDXGFCfKcAmyg2po8U34+RpS9seXphP5vPVpWx6OCrpYGfNwt8TWXM8g0ld/HhvdHskzXw2QpSFWLtlU+zcC7duc265/6ysLA4ePEh4eDhjxoxpMSHXavPQanPw8pnKK0deYW/mXp5s/yTP6uWI9r4JK/pSOWYV72Xb0M3BlnEelmMc5RbFk5FP8vXFr+nj14eHWj90mz01DQcbGbP6BDKjVwAHkgr5/mQGS3Yn8+n+VEZ18LaUOb3sMZWWoktKoPyjVxFJRNj27HFX+7sZNlHuSOzklPyQxJOaUVzySGDRqUUMCBiAjcyGy0dyUTpb4R9xdxdqdwJrax+UynYUF++jlf+sv3x/TSGijw9nd2dw6VAOUQP8SDpZQPt+Ptg5N84Ls+7YEYqLEWpqwMGhTtm6UxTqDBToDPhby3FqpqRZr5bV+9FuBM66OXuSlZVVd39OTk6jUuV3333H7t27AejevTtarZaSkhLc3d2xsrJsMzo6mqCgIFJSUoiJ+ftn7t4OVUYzVmJL9Mk/aIx/iFkL4R3iRM9xwRz9OZX4XRl0HnZ7ed5kNnHwrVlEagVCF36EjexPZa7OT0DJNTj1FbgEQ+eZOAxsRVLaJeTGPcgD4vg2UU+EawTv93qfNFFHft99nuHnFETtKGLb9W9JqSpAoejPgOgJRJdtJzT9B1h7CAbMg/bjmyzTtRR1wbJ+NxGz8+sttx0mg1YF1w9C6l5L8r66CBCBb2fL/kMGg2d7BEC1YweFH47HVFmJ84wZuD37TIOyn6etJ562ngxsZbnSNpgNJGQlsvbH36lwy6FMlsvn5z8HLNlqgQ6BtHdrT3vX9kS5RRHkGAQqI+VbU9GlViAPcMD5kRBqLhaj2puJWWPEZXIYohslQZEIhiyBqgLY9arF09ZuFNmJZcT9lk6bLh5E9K1XFvzDXej3WBgHf0ji8PoU+n2wCP2jk8h94UVabd6IOMKHqk4uBGU/Q/GyZWROehT7YcNwf+lFZGEjLMTs6k4CAvpx4sQJsrOzCQq6dVyBk62cYHclZzP//jyz6rh8BL0Z5Z/GL3UZHkjK6UIGJeqY7ZJOzxwjv5zNYWavAOYNa9s8gcq7gPX+VykyuXO4tC3jb0G0ampq2LJlC46OjowYMeKOPCjl5XHozPBB4iHiii4yN2Yu08KnWR70i4FN07H9YSiPBD7N5NGvN9j2rMhZHMs9xrsn36WjW0c8bO9+VJFELGJgqCt9bTSkO5USf/Qslas2kvxxIbqaYqx1NXVr7fw0SFJ+gU5T73p/N2AV6Ij7nEjEa64woXgY3/psYNHhRbwU+To5V8vpOjLw3jvMWwg3t4Gkp3+GXl+CXN644/Wvho29nDadPbh6Mp+aSh0SmZjoh1o3uVYRFgbFJZhrapA4tCw3sim4y6WojCZytXqUEjGyP51/69QypbxRbpnCTkbHDp1ITUklPT0dHx8fNm7cyIYNGxqs8/f358CBA0yfPp2kpCS0Wi1ubm4UFxfj7OyMRCIhLS2N1NTUOq/afxPMgoDaZGqWuP6Df4jZHaF9P1+KMqs4/Vs6bn52tI689clm/fb3iD5RSOXwHkTEDGh60eD3oSwNQ+zL7DOW8nPFFc4pzyE3ywjVdeZ8QSce6ziCK2IRyzIKeSA6EJuiA2iyA1FfdqPvIG+6jxmEQqEAZljUrH3zLR6qk19YYghuUzJqDueyKgh2V+JgU+v5MhktuVMuQbBtDmSdBLPR0t0Y/KCFiAU/CLb1V+S69HQK3llIzalTKKIi8V/9neUkeBtIRVIKdoloV9iTiU92wdHdBpVexeWSyyQUJ3Cp5BJ/ZP/BtmvbAFCIrAip8SdMG0CnAV2J6RGCVGmN/QB/xDZSKrZfp/i7y7hOD0esqH3biyXw8CrLTM2ts6gyurL3ezPOXrb0mxzWiBC07eGFukJL3I50bJ2siP7yS9LHjSf3mefxWT6e61nLkDz4NkGDdlGyahVlq9dQtX8/LjNm4GIXiPjq7/hPmIpYLCY9Pf22xAwgppUTsQn5mM3C3/aFKhjNVB/Pw6qNE/I/eSqVTlZEDfDFtDeLI2Ytv1RoeH5AMC8MbNM8gaoqtJj9bVzICHyGnB270VRXYa1srHoKgsC2bdtQq9XMnDmz9n3dcuSWHGdFiS0Z+gQW9ljImJAx9Q/6RHN2Uiylm2bx7rXPIDYLRn5uGZ9G/VSAcb+NY97xeawYuKJxF3ETMFWr0aenoU9LQ5eWXnubhj4rC2pLY9GA2NWNMncvTon8uSpzocZeQfdugYzhF9gzD4IHgn3L4khuBZmHLe5PR/HwahGHVafZLmwnJm8YYrGItj3vffsthZvrQNLTP6Wk5CDe3uP/tv3ejMgBflw9WUDahRKih7TCxr5plVoklyOSyzDX1DT5eEshEonwU8hJqdGSozXQ2lre4HNRp5Y1kU0okYhR2lvzwYKlDB48GJPJxIwZMwgPD2f+/PnExMQwcuRIPv74Y2bNmsXy5csRiUSsXbsWkUjEkSNHmD9/PlKpFIlEwjfffIOz89+rtLcENSYzZgHs/kn7bxaiv2I0xt+BmJgYIT4+/m/fr1Fv4pePzlFZVMO41zvj6NH0KKK4vFPkTZ1B60o5kQeOILFvukurQF3ApsQf2XrlB8pEAn42HkxoN4UHK7th2FHIbHsDWUYTZd1d6aQuJebCcRzs7Ii28yf5tDVSwcDolzrh0u6m7iuzGS5vhYMLLaXHwH6WiA2vqBb/nWazQKf39jEszIn3O1VaSpSJ26C6NqbOvZ0lbb/NYPDt0ijuwKzXU/rtSkpXrECkUOD+0os4jh+PqIUK3rWzRexZeZnuY4LoNLjprDVBEMjMuc6pvfu5rLpCimM216RZdcOc3W3cmR4+nSntplBzsYiyn1OQedjgOiMCid1NJ+iaMkwrh/DL9SeoEAUz7o2uzf5fBUHg8IZkEo/m0XdSG1pLM8me9SQ2Q/qQNuIonh4j6qIzDLm5FH28DFVsLFJ7BW7tinD48hLf/WQZD/VEC3KrtpzNYe7mi+x9oQ9tPFpmSr9XqM8UUL41FdeZEShCGneaVlZqWfvGCbJEJjZ2UvDJ0HDGNZdVZdTB2uFQeBlm7CFfbcWGN19i6HNzadurX6PlJ0+eZM+ePQwZMoSuXVs+BQAsHcFTtj9Ivt7M0r4f16mvN2AwCwyMT6baYOCEeT/yg++CU2sY/71lcHotNiVv4t1T7/Jq51d5rN1jgOX/biwqqidd19PQpaehT0vHWFhYvxOpFLm/P/LAAKwCApEHBmIVFIg8IACJnR1UF2H6fjQHi+1Y6/wvjucJOFtLWCR8yuA2DpY5ofepS82sM3Lyu928IH+XSRfm0zbSn4eevLPOz3uBIAicONkPpW0boqJW/m37/TNWvXQEXY2RGUt6YW3XvH3gclwcQUolirZtW3yeag5FOgP5fypp6o0mkguqcVbK8XFsuvnCqDdRlq/G1tEKW4f/zYHm+To9RToj4UprpP/DURlJSUm0bdu2wX0ikeisIAi3rS3/o5jdIaRyCQ89FcHmD+KJ/foSj7wWg1zR8DCWaEr45ct/Mz1HwPmdVxqRMkEQOJV/io1XN3I45zCCINDHszMTk4/Ro7wQ8dBhCDYuFKbqsdIWo0434HEhm0HyDHqPGEFUVBRSqZSg4HPEbshj27LzjH5RhEu72ggBsRgix0G7kXDmOziyxDLsuf14S4nRqWmiU4fKXErO/cZSwyb6JydCosYy91FhDzIbeOroLbvp1HGnKViwAH16OvZDh+Lx+mtI3VruedOqDRz5OQU3fzs6PNh0Sr5gFlCfzkcWW0hvIhk+dBS2XTwxCAaull0loSSBQ1mHWHJmCfZye0ZFjUKskFL6YxLFKy7hOiMC6Q2viY0zxxy+pEivYoj3Shytw4CmiZlIJKLvxDbUVOo5sjEFm6fa4z53LkVLluDUsy0FbCco6GXkcmdkPj74LPsYp8ceo/CdeeSf0lI+bjyhoyZwsCAfnU5X5wlpDjE3+cz+DmImmAWqjuQg87LFKrhxjEWN3sizWy6ilRnop5UxyN2R11JyiLG3JcDmT3+LIMDvL0DOaRj3PXhF4mk2Y+PgSNq5M42IWU5ODvv27SMsLIwuXRrOuLwd8qrzeGLPDIr0Rt6JHNuIlAGsyinmqlrLmojWyN1esIx/2jIDVj0IQ5dCxykIBgMjxR3JKWnL9c+WcFVxAqucYvRpaQ3UFLFSiTwwENtu3ZAHBWEVGIA8MBC5nx8iWTNZWKo8+H4kElUuA6f+xMDAfiTmqXhl60Weyn2WcVcOM//8Vuw6PXJHf3tzEFtJ6fHUUEYtvobcaM11zXEEU3hDr+VfCJFIhJvbQHJy1pN6bRGODp1xdIxBJrt1PMr9RP61CnRqS8NWbkoFwdHuza4VyeUgCJg1WiS2LZv92xzc5FIq/1TSLFJZ1DL3JtQyQRBAEJBIQGYlQaPSY20tqk26rf8R6tJvayNu6+4Xmljb+L6m7wdBMDextvZ1ISC2skLq7Y24uff2HaDaaMZGIv6fJmX3in8Us7tEztUydnx6gYAObjz0ZESdXG0WzDy3YyaPvRuHo18wYVu31V19qfQqdlzbwc/JP5OhysDRypGxIWMZHzoeH6UP5JyFtUMxenbgfORC3swu55KzJz6nsyivkLDjmR5E+DZUMHL2nyV2Yx4STIx+KRqXtk0QGU0FHP8ETn0Nghk6z4I+cy0BqABmE+TEW0z7KXuhMMGybcEVZfthOEYOB48I+CwKYmbCkMVNHhNjWRlFHy6hcvt2ZL6+eL79Nsreve742B74IYnkUwWMez0GN7/GZMRYqrF4ydIqsQp2xOnhEKROjUteBpOBOQfmcLbgLN8M/IauXl3RZaooWXMFsVyM68wIZB62JMcVsH9NIh27K+iRO84Sevp4bF2JqykYdCa2LT9PaW41o/7dAfM3H1B6dgfF8wwEBb5M69azG6wXjEZUz4RTdN4Ko8pAlp8free/Reht2tkFQaDz+wfoE+LKsgkdbrn2fkCTVErp94k4TwzFpkPDLzGV1sDMtWc4m1nOh6PbU7MtG6mdjHd7KWhlY8VvnUIamnlPfAF734S+r0H/1+vu3v3VJ1yLP8nTKzcgro2I0Gg0rFixAkEQmD17NtbWLY9zSKtIY9a+WdToVcx0rmB8z1+wt2+oDOVp9fQ6fZWejkp+aB+AuarKon4lXUK/5xt02Xnodc7oy/Vw06D5SgcpnuExKAKDLSpYoEUFk7q53Vn+UkUWfD8C1KUweRO0qjf7641mPtufzFeHr+EtLmfZlF50aXv/vEGbF5/men4mWyM/ZD2fEfxYF8RWf881uUaTQ2LSy1RWXkAQLJ2ptrYhODp2wdEhBkfHzigUf015VRAEti07T3mBGqlcgq2DFQ+/Et3s+sTLlwkAZB6eSN1a5okTzGaMxcUIen0j4qMXS0h3csFWp8O7vBSD0YREBBIRf1oLN08hNEoUaGzcUWhKkRnV93QM6iASWd6vTfw0dX+D+wBTVRUikQiZj0+z1Z+WwCQIXK7W4C6X4mV1/2fO/jfhH8XsPwDfMGd6PBzM8S3XOLcns85UuiphFf6/xOFYLdD6nfcQicUklyXz09WfiE2PRWPUEOkayQe9PmBQ60ENxqYYPCI53/49jly4yq92xVx392WK2ci0cgemSDXM35HIltk9GniNfB+MZohgZtfPBWz7+Cyj54JL2J/ImbUjPLjAQsgOfWBpNjj/I3R5Aiqy4dp+0JRZxgf5d4MH32FZRgDfX1NwfuwgEIsspM6kbzK7TBAEKn/5haIlSzGp1bg8+SSuc2YjvoMv1xvITirj6ol8Og1u1YiUCWYB9al8Knelg1iE09gQbDp7NPsFKZPIWNZvGdN2TeOFQy+wbug6gloF4fZUJCWrEyhecQnxsEAO/3gV7xBHuj3WAdK/hw0TLKn0j25uNoBWZiVh+DORbF1yltivEhjzr9ex+/d1VKmXyZasxd//CcTi+o+XSCrFYcRQ7Lw2UmQ/F+N3azDNeZqimTNxmTULibLpfDyRyDLQ/Ezm3xM0W3UkB4mjFdbtG34xlav1TFtzmsQ8FZ9P6sSwSC8SjVIOrbvKQrMbz1dVsjitgPnBtR1kqftg31vQdiT0fbXBtgKjO3Plj/3kpSTh2zYCQRDYsWMHKpWKGTNm3BEpu1J6hTn75iAWiVnQthtWVUews7OEcQpmM8b8fHRp6fx64gxPX09jhLqc1MxMTCUlddsQyWTI3bywUuRj18kRq4eeRx7Vk9OybJ499TKPR7TnxegX7/KIYpmT4A6HGAAAIABJREFU+8Mo0Klg6jbwbXhelkvFzH2oLf09tbz4czETvk/kyb46XhzYpsnYkTtBSU4VRRnVBHZ3QivoWKz6ikUrFLhOj0DSjN/qfsLa2pfoTj9hMulQqS5SUXmGioozFBRsJzfX0kikUPji6BhTq6h1xsYm8L6EjmYnlZGXWkGfiW0wmwSObU6lMF2FR0DTxEIkkSCSSDBrWuYzEwQBQ04OJpXK4lH7E7mRm0241agpslFSZqNEVqPB3lqOWHxrkiRDhF4jYLB1xsbOqX4tgEjMjQnrLSVa9+NYmnU6DNnZ6LOykDq7IPX0uKtyb7XRBALY3UVm3/9P+IeY3QOiHvCjKLOKU9vTcPWzo9glnV/3f8FHZ8D64VEcVGazMXYpF4ovoJAoGBo4lPGh4wl3CW+wHZ1OR3x8PCdPnqRCXcOxqAe57uDFfJJ5+oEJVGjSePpYOu9nVbApPpuJXRqmnvsN7MxQzhC7sYBfPzrHmLkiXMIadtMB4OADo7+E7s/A/gVw9GOwcbX4xEIGWsJXrS2K3K7Tf9CplbWFBAqCJbvMuxN4/Om1X79OwdsLqImPxzo6Gq8Fb2MVEnJXx9OgM3F4/VUc3K3pPKx1g8eMpRrKtqSgT1dh1cYJp7HBSB1vbwy3l9vz5QNfMjl2Mk/vf5r1w9bj6uWK++wo8lYmcHB1InKFhEFPhCOWiC3NCyM+s4TP7ngWxqxo1vNjbSdnxPNRbF1ylp3fJjFy8XJUi8dQElJMYdZ2vFo/3PAJYcMRx6/Gc2hbDkhm4XPoMKIVK6j4ZSvu/34BhzGjmzzZxbR2YveVAgpVWjzs78wMfyfQZ1ehT1fhMCywQbmrqErLlFWnSS9V8+3UaAaEWboVw7p5cmF/NoZDhUyd6M1X2UX0cVbSz1RgKRG6h8OYbxp1Brdq3xGxRErauTP4to3gzJkzJCUlMWjQIHx9m3jfNoMzBWd47uBzuIod+CLkDUqOvYlVsQd5O161+L/SMxA0GgAGAAalHVYhwcj79rEoXwEW/5fMxweRVGrpMN46CzIWQORn9A19hIdLT7H28lp6+/Ru0VSARihOgR9GWrx20367pc8zukNHYksP8N7By6z4Q8QfycV8MrEDYZ53r1BcPpKHRCZm5CO92b+jOyftT3Ii9yzdvjLiOiMCmfu9lexaConECienLjg5WUrUZrOR6uokKirjqag4Q2npEQoKLI08Mpkzjo4WkuboEINS2bbBRU5LIAgCp7alYeeioF0vb0wGM3G/pXHxYDaDZoY3+zyRtTVmtRpBEG5JaARBwJCbi0mlQubpidS1aYXNUxCoUmspsbPHWemIohlv2Z9hU6WnqkyLWWHbyCrzn4DYygp5YCDGwkKMpaWYa9TI/PwQ38aK8WdUmcyIRGDzP278v9dK5D+lzHuEQW9i64dnUZVp+D3qMx7emcZ1T4E/ethTpi/H386fCaETGBU8Cgerhm3YGo2G06dPc+rUKTQaDT6BgfwW0onTWiOLao7y+Jl58MhqhNAxFH5xnqeKS8i0EnFwbj+cm5jJl7MnjthNRYhFZsbMjcEl7DZBklUFYOtm6U68CZU1BqIW7mXuoDY8OyAEcs/CygEwfDnEzADArNVS8s03lH63GrGNDR4vz8Vh7Nh7Ms0e25LKxf3ZjHmpI961pnPBLFB9Ig/VngwQi3AcHohNTPMqWXO4UnKFx/c8TqBDIKsHr8Zaak3sFxfJvFJGT3spbaa2wzrippPrkaWWiIteL1jUxlugMEPFtmXncPK0ZVA/MxdyJyMzOdBj3OmGae5GPSwNhrbDOew4nsOHD/OvIUOoWLYM7cVLKNq1s+SfdW5IAC5kVzD6y+N8+ahFqfqrULo+CW1qOV6v15e6cis0PLYqjkKVllVTY+gR3PALKO1CMbu+SaDHpDb8S1GNSVPGH5eeQapVwZOHwLHp0Umb35uHuryMwXPfYtWqVQQGBjJp0qRbBsgay8vrzPdpF4+QcuEQfmViXMqNtZ4bQAQybx+L6T4wAFHrAF7SSSj18eXXAV2wut2VuirPQiqzTkLMTGoemMe4XVMwmA13NBUAgMIrFqUMYOoO8Gh36/UAJgN8258D5W68apqDSmvi5cGhzOwVcMdduXqtkbWvHieooxsPTG9HUWURw7cOR4mSNbkLkZokuE5rh1XA3cdD3C8IgkBNTXqdolZRcQatNgcAicQWB4dOdaVPe/soJJJbX6BcP1fE7m8v88C0toR1t3xmjm1KJeFwDlPe74HSqTGhSE9Pxwawq65GERqKuJmcQUEQMOTlYSovR+rugcz91v7ZzPIaKiSglIgJtLFq0bnLbBYoza1GbiXB4W8izy2FSaXCkJuLIAjIvLyQODq2+Hx8tVqDXCwi0Oavu8D8T0MQBEpLS6mqqiIgoGGs1j+lzL8JMrmEQU+2ZdFnqzFWCHw81IhILKKPRxQTQyfS3bt7o5Z7tVrNyZMnOX36NHq9njZt2tCpZy9eK9URX6lmeZgfk9yehMJY+HUOoun+uDzajpc+O8vjmioW70piySONr7x9B3dliHCSXZuL+fXjsxblLLRhOKEgCORWaEgtrCazVIO7fRGBbra0drGtG/tzLrs2v8y/1s92bp3F/B9hUYCqjx+n4J2FGLKycBg1EvdXXkF6l9MFbqAwQ8WlA9mE9/auI2WGEg3lW1LQZ6hQhDrhODYE6V12KoW7hvNh7w/516F/8drR15hmeJGMK2X0GBWIV3oFpeuTcBobgm3n2hmdvedCZS4cWw72PtCl+ZBMj9b2DJ4VQezXCRw960Sw32DyXHaT9e1btJrzQf1CqRzaDILkXQSMn8thoNDBgdCNG1H9vpOijz8mc8pU7AYPxv3luchr1aNwb3sUMjHxmWV/GTEzlmrQXC7Brq9vHSnLKFEzeVUcKq2BdTO7EN2qcedlQJQrnoEOXIjN4KuXIyhb/wxUZGGe/hviZkgZQFCnzhxc9x0/b/wJW1tbxowZg6BWoysowFBQiLHQcmvIz0OfkYk+LQ1TeX2em1QKnm4KfDr3Qhkcisa1knT9GiIfWo+TR30355L0fPZlFLKlQ9DtSRmAvbdF2Tr4Lhz/FJvceD564HUmnXidRXGL+KD3B7ffBkDeBVg3GqQKCylza2FgqUQGo77ggZUD2NOuNa9rJvN+bBL7kwr5eHwUvk4t/5JOOV2IQWcivDaPz93BnVkhs/gs7TPWRRziibQhFK9KwHlCKDaR9x5IfS8QiUTY2gZiaxuIj/cEALTafAtJq1XV0tKX166VY2/fvk5Rc3SMQSqtJ8xms0DcjjScPG1o07V+5m77/r5cPJTN5T9y6Da6cVSNr68vWVevUlhQgERvQGzTtLplqqzErFYjViqRlJZAaUmT6wCMJjOFKh1yhYRCEZTLJNi2sIynqzGg15iwLZJb1Pz/IggmE6bycoT8fETW1kgcHG57UW4UBPJ1BhylEnT3WKL/b4dCobgj9f/P+EcxuwdU6irZfm07KxNWUqGrQGFQ0jm3DW/8ayG+jo07H1UqFSdOnCA+Ph6j0Uh4eDi9e/dG4eLKpItpXKqu4cu2rRhdm0aOuhRWPQD6anjiANVJMj7YcYUN6NkyuzsxrZuOKMjZdZLYLcWIxRAwMZh0uYLUwmqSC6u4VlRNta7xWCmRCLwdrAl0s6VSYyAhp5Jvp0bTzlWK93cdEYUNw9jrXQoXf4hq507krVrhueBtbLt3v+fjaDKa2bzoDNpqA5MWdENuJaH6eC6VezIRScU4jgjEppP7ffFKrE9azw/7tjAi6VmCO3oweFY4gsFM6Y9J6FLKcRgSgF1f3xsvzDLsPGU3TPjRkuB/CyQey+PQj1cJ66FE5PUY1nEC4dGfYT9kSP2iK9tg8zSMj+1g8cajREdHM6T2cbNGQ+nq1ZSu+g6MRpynT8PlqaeQKJVM/PYkap2J356782aKlqB8+zXUpwvwerUzEnsrUgurmLwqDoPJzLqZXYnwaV5VybtWwa8fnaNbu1Siy17hhTav0Lb3LJ70szQPCIKAWaW6iXAVUJWaypWDB1AYzXhZWSEqLcWsbmx0lri6Im/dqi564pQ8m2Ulmwho05lPH/wcW5nFm5ecvID8gq306X0OsdjSOXa9Rkv/08mMcHfky3aNP4+3RfIu+HU2CAK7okbwSvERlvZdevupANln4MeHLc0j03aA810Y+fcvgGPLESZvZUtlKO/8logIWDAynLGdfG77WRAEgZ/fO4NIDOPf6Fy3XhAERv44klxjLj/1WY/TPj36DBUOwwJQ9rr9dv+TMBgqqKg8W6eoVVVdRhCMgAilMsziU3PsQsk1fw7/UMRDT0UQ1LFhA0vs15fIv1bJ1EU9kDUxp1EwGknp0hWH0aPxnP9Ww8cEgeJlyylduRLnadNwf+3V2x6vlzdfZMfFPP54uR+zr+eQqNZwuHMY3orb+/vUlTp+eOME4X186DPh7iYR/JUQTCZKV66k+PMvLB3oH3+Edfvm41g25pfy76vZHOocSlvlXzur9b8VLVXM/iFmd4Gk0iQ2Jm8kNi0WrUkLwPBsV3oeDSczYCw9xgbTcVC9WlBWVsbx48e5cOECZrOZyMhIevXqhZubGyV6IxMvXidFreXb8NY85PanL8DiFPjuQbD3QXh8NzkbMnkkNQcHFxt2vtgHmURMabWOlMJqUgqr6n4cL1yms94DM7DezkiNqz1tPOxo46GkjacdbTzsaOVsQ1GVjuvF1aSXqEkrVpNWUk1inoob497Gio/wsewbVuVMJuZsHDKDnrJRk7CbMYNAHxccrO+9fTo+Np24HekMndMeX29byjenoM+qQhHmjNPYYCT29y/PR12hY/WCw1SKSmk9HR6LehSwhKqWbUpGc8miGtk/1Npy0tXXWLrpCi9blA//W2drxf2WRvzODCJGb8MkjsVjoZKgVRvrQ3V11bAkEGIe54ficKqrq3n66acbbMNQWEjxsuVUbt+OxMUFt3//i++U4Xx9NINLbw/C9j531JnUBgoWn8Y60g3ncW24nFvJlO/ikEnErH+iKyG3iOkQBAFTRQW7lh0iv0jGCJfN7CQQdV4+D5q0KIqLMBQW1nm96p4nEqFRKDDaWOPTKRqpl6elG87Tw+LZ8fBE5u5miTCo3c/KhJV8fv5z+vv1Z2nfpQ0aZ07FDcHKyoOOHdbWrZ9w8ToXqmo41qUt7lZ3+T4tz4TN0yHvHDs9AvjQwYbNo35tfipA5glYP85iEZj2Gzg2HfdyWxi08E0vizft6RNkqyW8tOkipzPKeCjckw/Gtm/SznADBWmVbF1yln6TQwnv3dDSkJCXwGN7HyOMMH56dAPlm1PQJJSg7OGNw/DAFo+b+0/DZKqhsvJCnaJWWXkes9nyPjNpPPEN6FXrVYvB2roVIpGI3JRyti073+RxuYHMxx/HVFlJ4C+/NLi/5OuvKf70MxwnTsDz7bdvS8oyStQ8sOwPpnZvxdsjwsnQ6Oh/OplujrZsiGxZg8P+tYlcP1/M9EU9sLK593PtX4Gac+fInTsXY1Ex7i+8gPPj05tUz55OzORIWRUJPcP/qy8A/kr8Q8zuM/QmPXsy9rAxeSOXii+hkCgY2GogJ/NO4lklYf7nJdgNGMDlto+Tdr6YEc93QOFq4ujRoyQkJCAWi+nYsSM9e/bEycmiiBXoDIy7cI1srZ41EQH0d2nG5Jt2GH58GEPrfiR0+pwrG1N4y6gmwMmaKoOJkur6Acn2CimhnnaEeNjRIfs6FRdEiCUixrzSBZcQz6a3fxOMJjNR7+xlSHsvHu7ki//3o6k5VIKxGJK9QlgWMZYs2/qyh4utnEA3WwJcbQl0UxLoakugmy3+zraNRo40hbJ8NT+/f5rASFd6hDpRuS8DkUyC48ggbDrcYSTBbWAymdm+7DzFOVWk9tvHvqrf+aTfJ/T37w9Y/GwV26+hjivAtosnjqODLV9S6hL4bpClc3XmPnBtvrlBEAQOrbvK9ctnCXzobRwOOOB40onWW7cgrf2/s2ECFF7haPRXHDh4kJdffhlb28ZdmZpLlyhctBjN+fMYAoJ50/tBXn99ciOf171CtT8T1f4sPF7oxCWtjumrz2BvLWP9E13wFekwFBRgLCy03BYUYijIt9wWWn4XdDqqbb04HfMGfjkHCUnfTqmDE+UurkQGtUbh6YnU0xOZpwdSD08qZFLW/PorSisZ5ktxPLNqA3Lr5kt0giDwcfzHfJ/4PSMCR7Cw50KkN5nB9foyjh7rTFDgS7RubSG52wrLmZ2YyQchPszwvccynVEHe9+C0yu4pFDwY/iDLB6+rvFUgLTD8NMky+zVqTvuPcU/Kw5WD7aMbhv2ESazwKqjaXy8NwV7axlLH4mkf1jTuVz71ySSdrGY6Yt7Nmkef2PXG/xW9BuvtnqVyX0mUxmbTvWxXKzDXXCeGFo/uuz/EMxmA+cPHybl4n4CuhShM13CaKwAQC53x9ExBgeHzhxb0xqRIGfi/K5Nnl+KPv2U0m9XEno6DnHt57J09RqKlizBYdQovBZ90CIv7dzNF/ntYh5HX+mPe23Tznc5xbyZmsuyMD8e9bq9/aM4u4pN75+h+9ggOg26C9X3LiEIZgyGcvT6UvT6Eqyt/bG2br40Z6qsJH/eW1Tt24dt7954L/qgQUOEIAi0P36FPs52fHU36vX/CP4hZvcJedV5bErexC+pv1CuK6eVfSsmhE5gZOBI5p2Yx7HcY6w/Gon4TAJBu2IRHF1Z/+EhivQpaGTFyGQyoqOj6dGjB/Y35b9ka/WMu3CNYr2Rde0D6eGkrHtMrTOSWlRNSoFF/UourKJd3q+8bvqaNcbB7DbOQIKIeIwMivSkg58TbTzsCPW0w92uobk0+7cj7Pq1HLFEzOhXuuAacuv5f1fyKhn22TE+Gx1Kt31rKd2wBYmtNe7z3sZh1CgMJoGsshrSblLZ0kssStvNBFEsAj9nm1qipqwlbrYEuirxsLe8RsEs8OvH59Dlq+nXWokpT42inQtOo4P/klb+Y5tSLV1ZT4TjE2XHzD0zuV55nTWD1xDuaunUEgQB1d5Mqg5lY93eFecJoYikYihLh+8GgswaZu4Hu+aPo8lkJvarSwiu87B3K8JjrhabqE74r1ppCR89tw52PEv2qF/5bvsRxo0bR3h4051igiBQtWsXBUs/wpSfT2FUN3osfQe5f/P+rZZAMJsxlZaiz82j+KvjiOVqShy0nD5zFS99FaESDUJRIULtSKE6SKXI3N3riZajLbLrG5E62nDS71PSMwQend+ZBJnAIxeuM8HTmU/a1r9WvV7Pt99+i1arZWT/Pvy2ZCEjX3qDkC5ND/E2mU28c/Idfr32K4+GPcqrXV5tRIiKiveQkPA00Z1+xtExhiqjiV5xSXhYydgV3QbJ/SL3l3/BsG0O1WY953rN4YEBN/nNUvZayt4uwTB1Oyjvk2dr12sQ9zU8vqsu+ywpX8ULP1/gakEVk7v68+awttjI68mXttrA2teO07anF30nhTa52RpDDQM3DAQD7Hh4By5OLlQdy6VyZxpyf3tcprZDYvvfqdA0B4POxLq3TuLkYcPoFzsCAmr1tTpFraLiDDpdPpUZ3ck/PYPwEQdoHe6Ho2MM9vbtEYstCmz1kSNkP/kU/mvXYtutK2UbNlC48F3sHnoIn4+WWjp4b4Mbatm07q2ZP6K+6cMsWD4XCVU1HOoShm8LSprblp2jsljDlPe635PXzGzW1xEtvcFya9CX1t+nL0VvsNwaDGUIQn2en0RiQ6eO67G3j2x2+4IgUPHzzxQuWozYzg7vDxej7NkTgKRqDf3PJPNJmB8TW0BI/1fxDzG7R5wpOMMPV37gSO4RAPr69mVi2ES6eXVDLBKzLnEdS84s4T3ZONos/Am3F15AM3QIR44cITU1FZEgwVnSminPjcLRqaESll6j45EL16gymnjP2wOpytCgFJlTXl/2sZKKCfFQ0sbdjqnVq+iQvY7yfh+QVzCAsRfS6NPKmZVzbu3zyvntD3b9Wo5IImH0q11wDW6eVKw7mcGOFVt4NyMWoSAfh0AN7iv2IPVr+gR/Myo1hlqyVk/arhdXk1GqRmsw162zlUsIcLOlk1ZCzxw9bW0kIJegHBGIU/Sdd1y2BKnxhexddYXIAb70Hm/xa5RoSpi8czI6k44NwzbgraxvlKg6mkPlznSsQhxxeawdYisJ5J6zjBdyCbIE0Fo1X+LTa43sXLMS+9CPcCuZhmz+TzhNmYLnm29YFLiPQjD1epEP4yRERkYyfPit/WtmrZZlsxYw8MJurDDjNHUKrrNnW8b8/AmCyYSxpBRjQX4DI72xoKBW9SrAUFQExoZeQ4NIQqXSCc9gP2y8vZF5WUqK9eVFD6QuLvWdpno1fDcYKjLhiQNUSfxZP/8UIZ3deWBaOxan5fNJZiHftKv3TW7bto0LFy4wdepUWvn78/WsyYR07cng2c83+jsMJgOvHn2VfZn7mB01m6ejnm7yvZGS8i65eRvp2+c8YrGct1JzWJVTQmx0Gzra39+ONqEkldw1A/FWl1PRZSbODy2F5FjY/Lil63LKtvrg5vsBvRq+6g5iKcw5brkwAHRGE8v2pvDt0TRaOduwbEKHumad8/uyOLH1GhPmdcHVV9nspn9P+p3XT79Of3F/Pn3sU0QiETUJJZT9fBWpowLXx8ORuvzf8QKd3Z3BqW1pjH05Gq+gpj2RGk0upSWniV2uwNo5G+8eHwIgFlthb9/BQtJE7SgZ8gJu//43Und38t94A2X//vh++kldaf12eGnTRX6/1FAtu4FMjY7+Z5LpbG/LxqjblzTTL5UQ+9UlBj0RTkhM/blbEARMJvVNhKqWXOlLawlXSQMSZjSqmty+WGyNXO6KXO5iuZU5N/hdKrXjavJ8TKYaYqI3YWMT0OR2bkCbkkLuiy+iv56GyxNP4Pb8c6zIL2fB9TzOdm+HTwvI6P8q/iFm94hPz33KL6m/8HDIw4xrMw4vZX1Z4nLJZabsmkJfj548uzyNAqUt14YOJSMzE2tra7p3746HbRD7VyXTprMHfaaEkVFaQ0phFScKK9kg1mI0C8jiS0BlUSRkEhFBbkpCPOwI9bhxa4efsw2SG54Ps6nOjC6M38ySLTK+VlezamJHHuzg3dSfUYfs7YfYvb0SpFLGvNy5SeXMUFjE3jmvEJgYhzwwEK+217CJ7giPbrynY2k2C+SrtKTXetjSitXo0lVMytbjLBVzWDDwsUhLOQLudlYWZe2msmiAqxI/J2ukd3m1WJavZvPieFx9lIx+sSOSm0qs1yuuMyV2Ch62Hnw/5Hvs5fUkWh1fSPnWFOS+drhMD7coCKn7LKXIwL7w6CZLF10zUFdqOHasP0aNE2GJA9FvWInX++/j+PBYWDMUNOWsd3iWsrIynnvuudv+HfO2JfDHiSQ2is+j2rYNibMzThMnYFbXYCisJV6FhRiLihqk14Nl3IzU0xOZh0e9n8vDg+q4auKt7XjfKME3wIu1M7rhdAvvUh3MZtg8Da7+bjkOIZYRSMe2pHLpQDYT5nXB3suWMedTSVZr2d85lPLkJLZt20bfvn3p399SPv79kw/JSbrMU19/36A8pDVqeeHwCxzLPcbLMS8zNXxqsy8l7vQIZDIHOnX8kYSqGgbHpzDF24UPQ+/S33UblKhyOPVdb4ZXlmF2C0VcnAq+0TB5iyXM+X4j7bAldqPH8zDo3QYPnUor5aVNF8mv1PBs/2Ce7R/MpndPY62U3zLl/gYe2/oYl1WXWd5+Of1jLP8TXUYlpT8kgliE67Rw5E1M3/hvg67GwLp5J/EKcmDYM7efCXz693TO/J7OuHlhYJVARUU8FRWnqapKBMy4LZSBixU1bTXYS8IIfHkFCmXD0rQgCBxOKWbL2Rx6BbsysbMfIpGoTi2b3qM1bw1vOiJlbW4Jr6Xk8FGoH495u9y0TTMGQ0VDUqUr4fyBS0itq/BtK6ojWnp9KWaztsntS6UOteTqBsFyQS5z+dN9rshkLkilTYdb34yamnTiz45HIrElJnozVla3VoTNGg2FixZTsWkT1lFRvP7iW2Qj5ljXtrd83v86/iFm94hqfTVyiRy5pOGXlEqvYvxv4zGbzSzIH8LZlOuUurqiVCrp1r07rq3bklGuI7mgmrIzxbhnajlsY+CM3IjZToY+xgWpSETfMoEYF7vaEqSSVi62yFpCPHTVsOYhKMugethOhv2Uh1EmZv9bD2Atv7XEnr3tILt3qEAqZfQrXXELtny4BJOJ8p82Urx8OTqtjjO9xjDjuc6ItjwGEzdA2LC7Po5/hmAyU/VHDhV7MzEIArbDAqkMsSetRG35KVaTXlJNWomaipr6MppMIsLf2YYAVyVBN3naAlxtcVXKm73q1GuNbFkcj1ZtYPwbXZrML4rLj2P2vtlEe0bz9QNfI7uJbGmulFD601Wkzta4zYxA4mBVV4okahKM/vqWQ6eTr3xNTuFHFJ95l05Xj2COP0GrH9dhXXMc9rzO8Z7r2Hf8HC+++GKDUndT2H4hl39tvMDO53sRWJZD4eJFaOLPIlIoLIrWDeJ1o8zo6Vl3f1NZQ5orJaxbd5HFIi3RrZxYPb0zdooWlq8OL4bDi2DQe9CjnlRqqw2sm3cC7zZODHs6kiyNjgfOJBMgl9Dr4Hb8vb2ZOnVqXV5Z4tFD7PriYyZ/sBzPIIt3T21Q89zB54gviOft7m/zcJuHm3wJAAZDJUeORhMQ8C9at36W4edSydLoOdY1DEfZX5cGdDj7MPu2P86CkjLL+2XCektQ81+FHc/D+XXwxH7waUi4qrQGFuxIZOu5HPo52NE508iDj7cjtOvtPaXZqmxG/jISb503mx7bVOd1NBTXULL6MuZqA86T22Iddh9VwL8Ap7Zf5+yuTCbM64yr7+2JZI1Kz/dvHCe8pzd9bir3Go2iSQOLAAAgAElEQVTVVFaep+jlBZjP5VL4oQlBZlH7bWyCcHSMwc6uM6fzQ1h1vJzEfBU2cgk1ehNDIjxZPDaSd36/ws5L+Rx9tT/udor6EqKhXsXS6Up5Ji+IJL0DX9t9j5MpvckSYj0kGDRKlPYe2Np5/Ilo1RMumdwFucwZsfj+qFJmk5lzezLRVhsJf7CaC5emYGsTSKdOG5BKm1djb0C1ezdZC95h+Duf8IjYyEcDe96X1/V/Ff8Qs78AgiDw0uGXSE5Kpp+mL+qqGhR6A2V+0VzWOXOtRIPeaPkQi0Tg72TNoHIpDhVG1CO9WWmjx14mYUuHYAL/PPD5TlCZawl8lcg54PsDM8/m8VSoJ68/fvsr5JxfD7DrNxVIZYx+pSt2+mLy316ANiEBWdduTLHrx4zxvZmVOw9yzsCLibdUhe4E+nw15VtSMORWk6s3Yz2wFZFDWje7vkytJ72kmus3fGzFFrUts7QGvam+NGqnkNYrbDcRttYuNhz94SrXzxUx8t8d8Q11anZf269tZ97xeYwOHs3CHgsbkBjt9QpKv09EbCvFdWZ7ZK7WcPhDOPyBJe/sgbea3a7BoOLose5UZERjyn2a9n8sRKJT0/q75cjW9yev63y+jati7NixREY2798AyCmvodeHh3hnZDjTerS2xFCoaxDb2txV+ffLJcdZWlZBr2BXvp0a3cCndEskbodNUyHqURj9VSNiGr8rg7jtaYyZ2wnvYEe25pXwTHIOXfLS+HHEgw0IaI2qkm+enEK3hyfQY9xkVHoVc/bP4UrJFd7v9T7DAm99UVBccoBLl56kU8cN/K4J4uXkHD5v6884z7+YSMSvYcHJhVxSyFlfLcValQf934ReLzaadHBfoK2EL7tZFLkn/2hyVNjuy/nsX3UFT50Il0mtmdYrsEWhtMtPLmd1ymoetXqU1yfWzzQ1VekpWXsFQ141jqODUXb968KN7wU1Kj3r3jpJQHsXBj0R0eLnHfg+kWtni5i2qCeKm/x01UePkT17NphM+G/+CYO/iYryMxSXxbMrSWDn9V4U1rjjZVvK+MgCRnXwZsslBStOKnBS6OnlvY8+rXLxstPcsoRYKvLlFT4kVJLHhw57sJI7N0m0rOSuCCYlP7xxEt9QJx56qvlIivsJVYmGfauvUJBmef1BHd3oNKaEy1eewsmxG1FRq1pEAI+kpDM+t5J3v/6I4aEBeLzxxl2N6/tfwD/E7D5AEAQKVFqSC6pIyVdx5upm7EqLsTfYI6nR0+HyRRYFjkPk60+Ih5JQD7u6EmSwuxJruQS9xsjib86yKkKOp42crdEh+N2PGnveeVg9BMEjgqcL32RfdQ07p3clNOz2HXvZv+xj92/VCFIZdpUZiGRSrIKC/h97Zx0fxdW+/e/sZuPubiRAAiEhBHen0FK8LcWtxUqVUkoLlCIVaEtLkRZapBQvbsUteAIJcXd3W533jw2SEsMeeX/P9flsdjN75syZ2ZHr3HLdFBmYcTe9mLYuxphlXECw9ECw89HWZYMHfwSBR5Zpb/zCg9ptj7QVBKrVk1BmVqDMKEOQCuQpRdT6Ujxb2yIR7q/8cD3h/j/VfT5YXv1BRKS0SkVRpZKiCiWFlQqKKhQUVCgprdZoEwEzjUArhQ6pLrqYtrbCy9YYb1tjvGyNa7UMrQldw7o765gVMIu3/N+q8Z0irZS838JBELCe1BJdByM4NAdub65REaE2REV/Tkb6bmIPrMDB0QavHe9g2NQL166poG/E13m98PHx4dVXX633dxNFkU4rzhDkbsmPb7Sut21D+HH/PVZeTaKXnSlrZ3dqfE3GzLvaTEG7FjD+MMhqKR4vV7Pt82DMrA0Y+mEghw8fZmWphmgHN3YHNKGLRU2Lxp+fz0WtVDBw4ee89fdbxBfF8033b+jt2rvB4cTGLiMtfSst2t+k280EfIz12Rfg9WLT8a+ug+MfU+HVh5EGleio5OwRnJBFHACvvjBsw/ONM7uP6OPw52uPFYW/j/IiOZvnXybTTsbWyhK6elvzzQh/7M3qV1lXqBUM3DGQssoyNnTeQCufhxMEjVxNwfZIqqILMenpgmk/t/qPrbwMcqO0VQ9yIrTvinLov7RG4fbniYs7Ywg7n87ohe0xt2t8TOH9jMdH5Y3Kr10nddo0dJycUCYk4LB0KbqvDObP66n8ciGBrJIqfOx1GR2Qj5/lZUpLbqJQ5ACQWOzKursTKai0YITvHUYHZGOgX4dlq9qFuCU9j7kxaXzV1JnxTvXfu4P/iiPkZApjlnTE1PrFEpuY61mc3x4NQI83m1NRouDS7lg8/K1p9XIs0bFzsbN7hRa+qxD+mZ38D3yVkMnq5Gwu3LmAYv06dD09cVq1Cv1m/3nabC8a/yNmz4jvT8Ww8WIi5XIFXtI8/HTSMBHUlMrkOOo2YcCmVahfH4vHxx/W6/45m1/CxLBETEpUzInRMGFOIDrPKxU94iDsGku2xyT6RPalmZ6MXQt6IWlE/6l7TnJpTzyitQM69vYIUikZRVXkl8nxNZVryzVZNwWp7oNqN6J4/8/DCjiiRkTkH8tFELV/ENUimgolGrWIIJOg1IioVSJ6hjpaKYpH2tbsj4f9Pvj8SL/VY7m/vC6U2OpywVJDfF75A2smgKOZPl52JnhXkzVvOxOa2Bjx9a1FHEo4xPKuy3nZs2ZAvjKngryNYWjkaqzHt0DP1Qh2jIa4v7WurOYDax1DWXks164NwFiYws2d7fF2V+P8+zuYd/bGwfkCO71/IDu/iDlz5jT4u83afptbyYUEf9IwaakNoiiy6u8YfjwTR1+pLj8t6IFeY7XoynLhl54gamDq2XozU8MvpHN+ezQtBppy7vZhgrp0YYWJE2UqDafbNsPqEevctf27OblvIzdelZFRmckPPX+gs1PjXB7XbwxBKjVgi8FX7M0u4HTb5jQzeoHlXi59D6cWQvOXYcRv3CmMZPyx8Qx0f4llBk3g+CdgZAsjfweXp6it2RD2ToV7+7RWM/ua1qEbRxK5fiiR0YvbczQpjy8PRyKTCiwd6scr/vXHoF5Ou8zbp9/Gv8KfXyf+ir7+w2MoqqtlZK5nYdjaFovh3giCGvLjqglY5EMSVpT8sFOZIdj6QHkuFKdBz/nVFsXnJ8VRkl/JHwuv0ry9PT3HPnn80v5VtynOq2Tsko5U3b1DyuQpyBwdcP39d+JfGkiqX0fmug+isEJJew9LZvb0oqu3dQ3B3qqqDASJlPQiPfp8dwVPGyPic8vp6GnF968H1Fvf9r7e3s2SCs62bYabQd2elLLCKrZ+GoxfT2e6jHy6esQNQVGl4sKOGKKvZmHvaUbfSb4PSGDYuTQu7IjBzc8Kn/5XSUr5GleXyXh7z6+3z0G3YhCAw22aUh4cTPrcuWiKS7D7ZB7mr7/+f0rT7H/E7Bmx72YSoSEhyPJiUcsrKDMoI9kmmXWjfqZ47FuoCwtpcvQIEsO6Z2jHc4uZdi8JbyM9vpaac3VDBM072tNrnM/zOxkvfQenFrHJeg1fpFmw3MeJN8YHNGpVUaOpEXA9Yu0VNKLIPvU7WoHMScefeliiSkPJ2VRKz6YiMdTBYogXOQgc/ukOQYPcaf/KU6ihN7TNGiROS9qk1XF7KrWG1MJKYrNLic0pe/Ael1OG/BHCZmsqReLwK5WSeN5w/ZLeHh3xtjXG3FBr5VQVVZG3MRxVoRyrMT4YeOppMzVzIrWConU8jENCxlNeEYckdxMhx9NpYZ2F3Z4l2LUpImbIPI7fK+Tdd9/F3Lz+4PHfLyey6FAEl+f1wqmRBZEfPT5fHolk46VEXkHG4p7eWPavP8PqAVRy2DwYMu9ozwvH+s8xtVrDHwuDKSouxNA/m4kTJxBRIWfQrVh6WJqw2c/jwTUQHnOdaafeQmks5ed+axtdLFylKuX8hUCK7D9hZnYgs11t+bRJ/QTkqSGKcP5rrfu65XBtcftqF//PoT+z9s5abVUAXTvYNR5K0qHvEugwvd4YxCdGeT6saafVSptyGqRagqtRa9i6IBgLe0MGz9FaUxPzynl/VyghKUUM9ndkyastMatHpHT28dlcyLrAu+bvMnHIxIf7XZyGmH0PefAVNPGh6OqnIdWkIqir5XEEqVYmxM5XW7je1kf72dxd69aVl8KhdyF8D3j2gKEb6iX1T4IzWyKJuZ7Nm190wMTyyQn5/VqvPV8yQ/rldKSWFhis3cjmqFLcvv4Uy/IC9sz8hhk9m9RakuxRvL8zlKPhmVz4qCfnY3L5/MA99GUSvh3pT2+fuvc3rUpBj+tR+JsYsjugCZJ6zpeTG++RFJbHhOWd0TV4vjGU2YklnNx0j9K8SoIGuhM00P0xeY57F9M590c0Lr6WePU+RGb273h5zcPNtfaSdcVKFT6XwpnjZsfHnlpXuCo/n4xPPqH8wkVM+vbBYckSpA3c9/5/wf9qZT4jJGmhSNLv4OzmRrR5NKdKTrFxwEYkh04hj4zE6btV9ZKy/dmFzIxMppWxIX/6e2Iu00E1qIKbR5KwdTPFr8fT19Gqgc7vQn4c42/PYo/eH3wbmUGfCGdsfBt2aT5KyuQqNXfTixnfQhei47Qz26eEIr2Mwt0xKLPKMWxti9nLnqilAucWX8PC3pCgAe5P3Xd9qOFKpebNTUcqwcNamzTQ7xHJMLVGJL2wkticUmKyy4jNKSU6ZyrJel+zLXEx68/OQFTYYGOi98C65hNkSbsb+eRvicByVFMMR+/SapxtH1UtQOv12NicXcZx9+40WnSMpaLQk3vXQNZ9PFzcjL3POcCfxMREWreu30V5vwzXzaQCnAIaKFL/CNQakQX7w/jzeiqj7c2ZnqvBrFMj1xdFOPI+pF6FEZsaJGXaVTSUGycizXMk0L0HUqkUPxNDFjRx4PO4DH5Lz2OSsw3JJcm8d+dTFHoi4/O7NJqUARQV30KFwPfFATjry3jPveFg96eCKMLpxdpJUMCbMPjHGlafqa2mcin9EkuCl9B68D7s3joP+2fCiU8g5Qq8ugb0n1OhcCMrGPgN7JkIwT9Bl3cBSA7Pp6xQTpdRDy0pHtZG7H6rI2vPxfPD6ViuJxbw7Uh/unjXfm/4vO07DDx8mcOZaxn2x0XMqtK0Ew55CQKgD2iMHJBXOCE3aIt+365I3f3ByrtWl/YD6JnA8F+1mcxH52orGgzbAE16PtOhKMwqJyo4k1a9XJ6KlAG4t7LGxExKyO47uFg7c/TNuezbGIZKo2GhT0vcz+5mw7BmSBtIzInPLWN/aDqTu3hga6rPyCAXAt0smL09hMmbbzKxszvzXmpea8iAs74ui72c+CA6ld+rr4u6ENDHhdgb2URcziCgz7NpGd6HqBG5fTKZ6wcTMTTXZcgH2tjQ2tCiqxOCRODstihE9SDceuQTF7cCXV0bHOyHPNb+SlEZGqCb5cPwBR0rK1zWraNg8xZyVq2icugwnL79BsM2DcdI/1/Bf1Zl1P8gdO7cmYkTJ2LS2YQjJUeY2Xom/rqe5H7/A4bt22MyoO56eX9m5jM9Ipm2pkbsCmjyIDus3SAP3P2suLQrloy4ouczUEGAQd8h9ejCcmEphYh89ecdNBXKhtd9BPcySlCoNARWXAZdE2jx+EXWEESVhuKTSeSsCUFdrsBqnC+WrzVDaiTj6v4Eyork9Brng1T2n3PaSSUCrlaG9PaxY3qPJqwaFcCRWf05Oup3LAz0cfPdzrv97enR1IZyhZo9t9KYdyySl/NyuK1RkrcjitVrY1hlv5xKtUjV70PIy0rln5Zoa6seGOi7kpa2hZ5jm+Pc3IK70vYUuwUi3x2Bob4eSUlJDY63ub0JRrpSbiYVNtj2PlRqDe/vCuXP66nM6OzB9FwNxm3skZo0Mtbx2joI2QbdPnpQyL4hnDx5kuzKOEztZYSdzkKl0GaaTXW2obelKYvjMziREc6E4xOQq+XMZjhiSBoqhaKBnh+iqPA6J4TBxFZJWOrtjOGLKPQsilr35KXvoM1EGPzTY644mUTG8q7LUWqULLi8AI2+Gbz+B/Rbqq23ub671tL4vNBiqNaVenYZ5MUCEH4hAyMzXdxb1SRdOlIJs3t789eMzhjpSRmz8Rpf7r+NPOU2hG6Hkwtg6zBY2RybH4N4Nz+bGMNKLmWcQoMArUbBoJUw8Th8nIxkXhTC2D0UVY0n56w3SjzrJ2X3IQgQOA6mntHG320dCme+1NajfUpcO5iIjq6UNgOeXklemZyEXvxZiozd+bjlFPZFFjIiyJmzH/ZgxDhtDdvKO3cb7OenM3Ho6kiY1u1hcfQmNsbsm9GJCZ3c+e1yEsN+vkJCblmt6492sKSnpQlL4jNJrpTXuR1bN1McvMy4ezYNzSMJUE+LskI5B34I5er+BDwCbHjt03Z1krL78O3sSJ/xPqTHFJF4ZgwmRp2JjPyY/PyLj7W9UFiGoVRCm3/oCQoSCVYTJ+C+fTuCTEby2HHk/vwzorq2jNT/e/jPeUL+h8HGxoYqkypWXF9BR4eOTPabTO73P6AuK8N+wad1uiI3peXyXlQq3SxM2O7fBJNHZkiCRKDPRF9MrPU5viGcssK6L8Ango4ujNqCv2UVo2Uh7FNWceWP8MfIQX24nax90AdmbIeWw0C3YW2bR6FIKyX7xxBKz6RiGGCL/XttMPDV6vNkxhcTdj4Nvx7O2Hs+J8vBC4armQtr+vxEmaqAG5WrWDK0GQdmdiZ8cX+uzOvF2kntyBvgSpK5jGH5GuR3dXm99D00pTlk/PwKnb44yKh1wcz/K4zfLidyOa4Qc+vXKS6+RXllBC+95YelkxF3mkyixMAFm/Q0EhMSGvzNdKQSAt0suJFU0Kj9kKvUzPjjNgdCM5g7oBlv6RshaMC4jjqBjyHuNJyYryUCPeqPJbmPiIgIrl+/TsdOHen5RkvKCuWEnUsHtFbN731cMFWl8NGZaYDA7wN+p1vgSyjlVaRFhDVuXEBMQRT7GEV/a1P6W7+A80qj0VoKr62F9tO1SR51ZFy6mbrxYdCHXM28yvbI7Voi0mkWTDiidQP/2hdu/vYwOPNZIAhasiTTh4OzKckpJyUiH58ujg9c99rxqyE/HiIO4he3lpNOG7lpNo9PQnqht6kn7J8O1zZAeQ54dIe+X/Day5vwNHBhsaUdh51marfTdgq4dXyg0abvbYHNW60QRchZe4eqJ5lk2vlqyVnrN+HCN9o6tMXpT3wIclNKib+dg39vFwwaO8H4B67diGb88oN81qQtCkFklKk5Fz/uybKhfrhZGaHv1wokEipDQurtJz63jAOh6Yzr6I6NSc0YMX2ZlEWDW/DruCAyiip5+cdL7L2V9lgfgiCwspkLOgLMiUxBU895EtDbldL8KhJC855qv+8jITSXHV9eIzuxmJ5jm9N/aosa2an1oVkHB/pM8iUzvpTUC7PQ1/UlLHwGJSU1SeyFglI6mhmjW8d1Y+DXEo99ezEdNIi81T+SMnESyuzsZ9qvp4EiLf2JnpcvGv8jZnWgQlnBh+c/xETXhGVdlyGPiKRo1y4s3hyNnnftgZdrUnKYH5tOPytTNvt51DqD1zOU8dLbfijlao5vCEOtfPZZD6CdhY7exVzDrVgICpbGZ1F6M6vRq99OKcTZUI2dOlM7s20kRJWG4uNJ5PwciqZShdWEFliOaoakOpZFrdRwdmskxhZ6dHj1+ceVvUi0smnFiq4rCMsNY/6l+WhEDYIg4GhuQPemNkzq0YSuH3XAMNCWsWpdfm4zgMQeq2kpSeZ345+RiEqO3M1k8aEIxmy8xvAtlsjVemw59S2fH42gtK0FgoEudwNmYpqWR0lpKQUFDROuNm4WRGeXUlJVv1W0UqFmyuabnIzIZvHgFrzdyYPy4Az0fayQ2TQiey0vTusys/HRxlQ1QgaisLCQAwcO4OjoSO/evXFuZoFrC0tuHU9CXm3FTS+6h37WUlTo4dtsBZ7mnri0aIWOnh7xt280PC60BazXlrdHFKQs8Wq8S7fR0Ki1WnU3N0GX92DA8gZjxUY2HUl35+58d+s74grjtAtdO8DbF8G9Cxx+F/56S5u5+KwwsYcBKyAlmHu7jyEALVyS4MpPsH+G1kq3zAl+DIRdY+HcCqQ54Vh7tCLdbybzdT6kn+Jb1nQ6j2rqBRi2HjrPQadpfxb3WEalThWbYzaTnl47adJ1NMZ2hj9Scz3yfgunIiSn8WPXNdK6d4du0FoS13WBmBNPtPtXDySgZ6RDQN8nc+eJosiFmFxe++k8r+2N456JI2+1tqBVVyf0M+UYax7+xlJjI/SaNaMytG5iplRrWPV3DHo6UqZ1q/v+1sfXjmNzuuHnZMYHu+/w3s5QyuQ1rYWO+rp84e3E1eJyNqXXTbrc/a0xtdbnzunUJ9jzh1Ap1JzfHs2xdWGYWhkwan5bfDs7PnHcc9O29vSb3IKcxHLSL85FItoTemcyFRVJgDZ2Lr5STjfL+vXOpMbGOH79FQ7Ll1MZHk7iq0MoPXP2qfbtSaBISSFvwy8kDhtOfJ8+VEVEvPBtNhbSRYsW/bvH8FTYsGHDomnTpr2w/pdfX87VzKus7rkaL7MmpM95F1GpxHn1D0j0as6KRFFkZVI2KxIzGWxrzvoW7ujV41YxNNHFws6QO6dTqShT4NHqORWlNrREz9kfuzs/sU0ThFFMEYH+9g9IUl0QRZElhyNoxz1essrV6nI14iJVpJaS99s9qu7lYxhop1UJd6hpabtxJJGEkFz6TWmJlWPDgoT/afA098RIZsTWyK1Uqaro5Fgz5V+QCOj7WCFWqVBcy8LS1AuD9r5Yh//KCG8pb0+bxZsd3OjZzBZfRxsqKjNxNzjPtrAADkeVcE9U4K/UQWHsQKlxMQlnb3JH34WSKiUyqYCJvs5jN0y1RmTv7XTae1jibl27ZbO0SsnE325wLTGfr0a04s32bpRfz6IyPB+L4d7omDfgfqosgi2DQS3XJjUY114s+1GoVCq2b99ORUUF48ePfyBWauloxN0zaYBAhnksM07PwM7Qhm5+X7M9T0pzI32amxqRFRdDelQEgS8NbvAhcSDlJhuK3Jltr2CQg3uDY3siqJVaAnV3J/T4RKtP1ojrQRAE2jm0Y3/cfoIzghniNQSpRAq6huA3EiQyuL4eIg+De1cweorrXl6qJTNxf0PWXdT5KZyK64+z7h1aJM+G+DNQmg3mLuDdH9pMgG4faollp9nQcjhmvr0JCurE3UIdfruSwsW4PDp4WD1IcLE3siejJIPgimAU9xR0bt35gSDwo5Do62AYYIsiuYSyS+mgI0HXzbTxD3j7luD7qnbMV9doZTXcujSYtZkRW8S1Awm0e8UDl0YK32o0IsfDs3h/1x3WX0hAnlfA2LgzrJ7Vlz5922Jlb8Sds6lIZRKcH+mzKjqK8gsXsZoy+UFMrkYjciOpkLXn4/h4bxh304qZ1s2Tvr71xzga6+swLNAZqSCwOTiJI3czaeNmWSNrs6WxAaEllWzPzOdVWwssahFJFgRtNnvE5QxcW1hibNH4+Lq8tDIOrr5Dyr18Avq60m9yCwxNn15T09LRCCtHY8LOZaAu6oWh/Xny8g9ha/cyJwoUnMgrYWETR2x0638GCYKAvk9zTPr1ozz4CoW/b0ZdXIJhh/YPS8A9ByhSUijcuYvspcvIXfUdFcHB6Dg4YDluHIZBQfXGjT8PLF68OHPRokUbGmr3P2JWBzzMPGhq0ZQ+bn0oPnCAwm1/YL9gAYatawY+i6LIkvhMfkjJZpS9BT/6uKHTCFFHSwcj1CoNd8+kYWSmi61b/cGljYaFG83M1NyITOGIxoxeiRVYt7XXSlPUgfSiSn48E8ebmsP4d38VXNrVuwlRqY0lK9wTg6AjYDm6OabdnBH+ETuWn17Gqd8i8G5nR2C/p48D+XejlU0rCqsK2Ra5DSt9K1pa15QpEAQBvaYWCFKBsssZKPHCoKUlwvV1CIBRs564WBoS4GKOt2NTMjK2MKlbK94ZMIKOvrboqKMoSrOiUj8Li5xkjoUUsC5WzqbLSfx6MYGT97K4mVRIYl45JVVK7E31+fN6Ks4WBnRq8vjDvahCwbiN17mbVsz3r7dmWKAzokakYEc0MhsDTPs0oEWlUWutLJmhMHo3ODRO0PLvv/8mIiKC4cOH4/pIkXUjMz2Kcyq4dyWdVaWfY29hy6b+mxhg787ZglJ2ZhUw1M4CfZWCyItnadqhC4Zmdce5VKo1jA9Px1TMZr1/W2TSZxBr/idUCtg7CSL2Q59F2ri6J7AkGMoM8TDzYGvkVpQaJR0dq+vYCgK4dwbXjlrCd+MXMHOhqlgXVX4eOtb/+B3VSsiNhsTzELZbq512erFWqiNkK8Qch9xo4hlEdFEgXZ2PYfbmSm0lhh7ztFUpvHqDQyswdYR/VDDRl0kZ6OeAh7URe2+lsSU4GUsjXVo6aYlVoF0gu6N3k6JMwbPCE3d391r3V5BJMPS3QZVfRfnlDDTlSvS9Leq939Q8YJYQMBqqirSxjPFntZmbdZS2EkWRU79FoFGL9J3UoqbrthYo1Rr23U5jzo4Qtl5NwUBHYGr8Kd65sZ2B3y7ArI022UbfSEZeaikJIXm06un8IBtRU1JCydGjGPfrS7RcxsZLiczbe5dNl5OIyS6le1MbPuzXjDc7uNWbTXkfEkGgg6cVHZtYc+RuJr9dScRQV0qAi7YyhyAIdLIwYktGPrdKKnjN3rLWa9XS0Yjwc2lUlSvxCmx40iSKImHn0jjxyz0AXnrLj5bdnRolQNwQLByMsHYxIex8JsqC3shsjlBUcpq/lN0pUGn4rEnjrXE6FhaYDR2Kprycwq1bKTt3HsN27dCxqFscvCEokpMp3LmLrGVLHyNj9l98gfXkSRgGtn7hpAwaT8z+l5VZB1xNXXE1dUVdVkbOtyvR92+F2dCaAfEaUeTT2HR+S89jvLrEBD0AACAASURBVKMVy5s6N+rivI/2gz3JSynlwo4YrJyMn1v8ldBmLEtSlzHgqpofMgv4+nQKZv3c62x/6358mU4itFpfb9/ylBIKd8egyq3EqK09ZoM8kOg/fhppNCJntkaha6jzwjR3/lUQBIGP231MZnkmy64vw8HYgW7O3R5rY9rLFYmhDkUH4smtfBmbVhkI57/SPhjbTADAyMgLS8uupKf9gZvrNDp4WoHrEOLjXmOXsi9ZTiJfHt9J+ZRfiNExIzZbK+lxMTaXvbfTHtkebLqUSEG5gqldPR9YznJL5YzdeI2EvHLWjWlDH19tmn7lvTzUBVWYD/Ro+Cb59+cQdwpe/l5LJhqB6OhogoODadu2Lb6+j9cHVLbJQHVDpHvOCD4c8ybm+toH77oWbvS5Ec3MiGR+D9BmZSXcvoG1S91EfnVyNhlqA5YZnMZQt/7i708EZZW2okHsCa2bsMP0p+qmh0sPhnsP5/fw3+nq1LVmpqlnd3j7EuLO8Qh/TaMy3oj8aBOsh/fAtF0TJPnRWk2wvFjQVLuqJTrazEfnthA4Hmx9tbFaZq6EfxeKqUkuLlXHoGigtv8nwKsBTrTzsOSj3XeZ/1cYpyKzWTHcD1sTcz5s9yELryxk6+2ttGjRAhub2rMFBR0Jlq81o8Rcj9LzaaiL5Vi+0RyJbiMtHTJ9bSybe1c4OBvWdYVXfwLfwY81TblXQGZcMd3faIqsnv4rFWp23khhw4UEMoqr8HEw5YchzWnx9ceo4mJxWb/usSxA/94uJN7JI+Z6Nr5dtLIreW7ack3Lv93NFutAdCQC3ZraMHdAc/r62mGk93SP0HYelhyd05W5e+7y5ZFILsXl8e1If6yN9XDQ02WJlzNzolL4NS2XaS6PEy9dfR18uzhy50wapQVV9WalVpYqOL0lkuSwfNz8rOg9zuep4/LqgkcrawZOb8WxtWFoglegbv8R5wxy6G3j8MQuUomuLvbz52PUsSOZn8wnccQI7BcswGzokEb3pUhOpuT4CUpOHEceEQmAvn8rbOfOxbR/P2ROLyD84TnifzpmDSB7xVcUbN6M+66dGPg9tByoRZEPolLZkVXA2y42LHyCWcGjqCpXsnv5DVRKDaPmt8XI7DnN/jUaVv7wDT9mt2Q1BvR/qw16HrUTv0X777LzahxhrQ+g89rmWtuISjXFfydTdjEdqakeFsO90W9a9ywm9FQKl/fE0XeyL03bviAZg38xKpQVTDg+gaSSJDYP2IyPVe2ClhV3cijYGYPMThdbs+UIyee1NUebaTN58/LOcOfuVFq2+AE7u2pisXsiB+6YEqJjgU+MjDYlwXjs2InU+KGrsrhCSVxuKbHZZWwJTiYqqwSZVEClgRGBzoxq68xHu++SWVzFL+OCHsgiiKJIzs93ECuU2H0QVL81I3S7Nii83TStLEMjUFxczLp16zAzM2Py5MnIZDXdFofiD7Hg8gJeyZyKY7Ivb3zeHgv7h/u1J6uAWZEpfOBuh/36Fcj09Hh98de1biuuooqe16NoL15kuUsZ3l6PK+A/FRQVWrHghLMNVnJoDCqUFYw8NBKlRsnewXsx0X0oF1B28SJZCxdibh2NtW/NeDONgT0SZ/+HmmB2vlpSVksJpoKMcv784hodh3gSmDkDssJh5jUwffLSSRqNyJbgJJYfi8JQV8ryYX70a2HHm4ffJDY3lgmaCcyYNKNWl+ajKAvOoOhgPDJnE6zH+yI1fkICUJAIeyZBxm3tOdh3yYOsT1Ejsmv5DRSVKkYv6oBU5/GxFFcq2XY1mU2XEskvV9DW3YIZPb3o5mRI6pSpVN67h8tPP2Lc/XECK4oiu5bdQKFQU9XbloN3MglLK2L78cUke7ZCnLeQl1raY2H0/EiNKIpsu5rMkiORmBnI+P61ADp7WSOKIuPCErlYWMrpts1oYvg48SrJr2TbgmAC+rjSafjjEj0AqREFnPo9AnmFik7Dm+DXw/mFCrqmRhRwZO1ddMyULO9sxUybK7zXZkaD1QHqgjI7m4yP5lJx/TqmL7+M/aKFSI1rD4lRJCVVk7ETyCMfkjHT/gP+Y8hYY3XMnjn4XxCEJEEQwgRBCBUE4Wb1MktBEP4WBCG2+t2ierkgCMJqQRDiBEG4KwhC4CP9jK9uHysIwvhnHdfzgDw+noJt2zAfMbwGKVNqRGZGJLMjq4D33e2empSB1oT+0tutUFSqOLEhHLXqOSUDSCTMnDYdF51iVlFO9h9haCprT02/FZNMgCQOncCxtX4vTyom+4cQyi6kY9TOHrv3AuslZSV5lVw7mICbnxXeQc9HSPI/AYYyQ37q/RNmembMOj2LrPLakysM/W2xHu+LKk9JTu77iDYttUH0abcAsLLqgYGBK6lpj5Dg5oPoqvMXAKn2bsQpvcj4+GNEzcPzwcxQRhs3S15v58rMnl5oRFg/NoixHdzYdzuN4WuDSS2s4IfXA2poVSkSS1CmlmJcrUFUJ1KuactMeXSH/ssbdUzUajV79uxBrVYzcuTIx0jZruhdfHrpU9rat+W9qWPRkUm5eiChRpsR9paMsLPgu6Rsqtp3JyM6isrSx+sLiqLIJzFp6Asio8XfsDBv36gxNgh5KfwxQus2HLL2mUkZaM+VZV2XkVORw/Jr2mOpys8n/cOPSJ06DUHfAMOPD8LEY/Dy91QEfUv8pQCiN+uQnd4WTZd50GqktvRVLaQMIPxiOhIdAZ/OjlptNbVcm0X6FJNtiURgQmcPjrzTBScLA97edpu5e8L4KGgBCqmCk5UnuXGj4cQM446OWI3xRZVVTs7aOyjzKp9sIJYeMOkEdJwF1zdo9QHz4wGID8klL7WMdi97PEbKckvlfHU8ii4rzvDNiWhaOZux++2O7H67E93dTEmbOYvKsDCcvv22VlJWWK7gz+upXBbklGRXsu1ADAALXvbFtkNb2lakMbq963MlZaC1tI/t6M6BmZ0xM5AxZuM1vj4ehUoj8k0zF/QlEt6NTEVdy29qamVAk0Bb7l3KQFFV896uVmm4vDeOg6tD0TOSMWJeEK16urxwlX0XX0tenuWPvFiHcWdKcMjeR1zciqfuT2Znh+tvm7CZ8w4lR4+SOGw4lWHhD75XJCWRt249CUOGEj/gJXK//x6Jri62H3+M15nTeOzcidWkif8RpOxJ8LyyMnuKohjwCBOcB5wWRdEbOF39P8BLgHf1axqwFrREDlgItAfaAQvvk7l/F0RRJHvpUiSGhti8996D5XKNhqn3EtmfU8Snng7M9XhyU+0/Ye1sTK+xPmTGF3Npd+yzDv0B9I1M+WJYIElI+KOsgsLdj0toVChURBRAG/2sxwQfNQo1RYfiyV1/F1GlwXpySyyGetfqurwPURQ5uy0KQSLQ/Y1m/9+V27A1tGVN7zWUq8qZcXoGZYraM+z0m1liPbklqnIdcgrnI+pbw/aRkB+PIEhwdh5HcfFtSkqq5SG8+2EhqcRMV0TXrpJ4j8HEhZWQt+bnWvsPctdeHnE5ZYzp4IqZoQxdHQkajcjsP0NYdjSS/DKtHEvpxTQkRjoYtamHJBenwc4xYOqkLSckbZyL5uzZs6SmpvLKK69gZWVV47st97aw5OoSujp3ZU3vNVhZmtG6nysJIblkJRTXaLuiqTNuBrqssWpCha4eSaG3HtvW/pwiLhaWMc08DjNKMDNrcOLZMCqLtJpaKVdh2C/aeKfnBH8bf6a1msah+INc/OULEgYOouTECaxnzsRj/19aV5pbJwiaiOHLU3HffwTzESMo2LSJxKHDqKhHpkEpVxN9NYsmrW21bimrJtBrAUQfhfC9Tz1mL1sT9k3vzOxeXuy7ncbszdn0dhxOomkiO8/vpLCwYf08gxZWWE/1Q6xSkbs2FHlSMaL6Cciijq62tuYbO6E4FdZ3QxO6k2sHE7B0NMK73UMLfGpBBZ/tD6fLV2dYdz6e7s1sOPJOF36b2I627pZoFArSZr9DxfXrOK5Yjmn/fg/WLZerOBCazqTfb9B26Snm/xVGhEyFqCdhppMth2Z3YUpXTyzaBqJMTkHViIzpp4WPgykHZ3XmtSAXfj4Xz6j1wSjLlXzp7cSNknI2pObWup5/bxcUlSqigjMfLCvKrmDv17cI/TuFlt2cGPVJENbO/7rEK+dmFtwdaItZpUjVxfeJj95HcsqvT92fIJViPX06blu3ICqVJL3xBilTp5Hw6pCHZExPD9t5WjLmvnMHVhMnIHN8QVVA/gV4ZlemIAhJQJAoinmPLIsGeoiimCkIggNwThTFZoIgrK/+/Oej7e6/RFF8q3p5jXa14UW7MktOnCR9zhzsFizAcsybAFSoNUwOT+RsQSlfejsxpR6F5qfB5b1xhP6dQq9xzfHp9PxOqrd/OcO5+DK2Yobv8CYYtX1YdSD4bhRvbI9nU+sEer02+8FyeWIxhXtiUOVXYdTBAbOX3JE0Ip4i8komZ7ZE0u31ps+vusF/IK5kXGHmqZm0c2jHT71/QiapPetIkVlO3qYwpKpUbHU/QjA0h8l/o9LX59LlTtjaDMDXt9pluG0E+1NMiJY2p6lOHzJjC/EP/Qm/JTMx7dv3sb67fn0GC0Nd0gorkUoEtk1uj75Mwg+nY9kfko6BTMqc1i4MvFaAaR9XTPvUEbelqIDfBkB+Akw5BbbNG3UM4uLi2LZtG4GBgQwe/DAeSBRF1t9dz5rQNfRz68eKriuQVZcvUlSp2PZZMBb2Rgx5v3UN4h5aUsHLt2PwTonhg6JkXn7nowfflajUdLkWiYOejC+FJYjqEtq1O9iocdaJigItKcu+ByN/A59Xnq2/2jaRlMDZ2a/jGVuKjn9LXJcuR8+rdrfTfZRfuULmgs9QZmZiOX48NnPeQWJQs/xWxOUMzm6NYugHgTh6VwfKa9RaC1NhEsy8/nRZn4/gVnIh7+8KJaWoAOtm32MglzBZbxLjxo5r1IRLmVdJ3m/hqPOrtAsEbTwaUgmCjoCgI6l+CaAjQXhk+f02UjEXo/TPkFWEkiHvg6rZp5i7WJNQKWdjYi5HMwoREBjiYcWkFk54WBo86Bc05H6/kvLLl7F5bzZmrwxCgcilhAIO3cvkZGQOVSoNDmb6DPZ35BV/R1o4mnLjSBI3Dify5uIOmNsZUnHrFslvjsH55zWY9Or1TMe0MTh0J4P5+8JAgOXD/NgjVHGuoJS/g5rhXUsd2D1f3aSyTMnoRe2JvprFxZ0xSGUSeo31wTPg+T6jGgO5RkPzi+GMFw1w3J+BVLcYp65LCGi7AHv7V5+uz4RESk8cp/jIURRxWikaiYkJlhMmYD5sKDKHJ3ff/zvwryzJJAInBUEQgfWiKG4A7ERRzASoJmf3oxedgEfFV9Kql9W1vAYEQZiG1tJWI+vrRUCREI+erw8Wr78GQJlKzdiwBK4WlbOqmQujHa0a6OHJ0XGIJ3mppZzfHoOlozF27s8nU/PzkR258O0ZVqtyWfGXCj0PS3SstRkot29eAexo3VWrcq1RqCk5nkRZcAZSC32sp/qh36RxdcwqShRc3hOLg5cZLbv9d5mOnxSdHDvxWcfPWHhlIUuvLmVhx4W1Pqx0HYywfduf3I1Scss+w0Y1H2H7KHQmHMbBfjjpGTvx8voYXV1raD4Ij7j1hOJGmwl2XN6sJFx8G71FP+Dn7v6Yfl6QmyV/haTjaKbPH1M74FGdALBqVAAzejThu1OxqK9lIUfGDlUVo+UqjP9JrkURDsyAzLswemejSVlpaSn79u3D1taWAY9UwRBFke9vf8+m8E0MbjKYxZ0WoyN5uE1dfR3aDvLgwo4YUu4V4Nby4XUUYGrIJ56OLBFhb3o8A9VqJNWp8l8lZJKrULG5pTNFIbdxcnpGy1ZZLmx5VVuI+/Xt0LRfw+s8AUSlkoLNm8n9aQ2eUgmbX9Ijv78Z65s0rOVn1KkTHgcPkrPyWwp+/52ys2dxWLa0RrD6vQvpWDoa4eD1SNyoRKrVB1vXFY7N1ZbPega0cbPg6DtdWXo0kl2RL1Hl9CcHc87jf8efgICGy3LJrA2wne5PRWguolyNqNIgqjWgErWfH7xEUD/8rJErofqzQqVPhXIZhqrNOOjuojwhhi+j57BDdEAfGIEur6GLbYICEhLJ/+cgDPpj1Kc/FWFQEXYdAJ/q14cYg46AVC5BuF2McLeUbB0JtqKIRICrq0No42ai9QxLpBRsO4Uyz6maOD5KLCUYtLBCZv9kotx14RV/RwJczJn9ZwiztocwtI0z+jYwJyqFQ4HeSP9xnwno48qJX8LZvyqErPhinJpZ0GeCL8YWzzFb+Qlws7icSo2Gjn62BLjZcXB1CGkXFoCwgrYdLbGy6tqofu6TsZLjJ5BHRwNg0Lo1tvPmIVZVkvfzWgp3/Ilh64D/GmLWWDwPYtZZFMWMavL1tyAIUfW0rW2aJdazvOYCLenbAFqL2dMMtrGwnj4dq8mTEXR0KFaqGH03gdDSCtb4ujHM7sV4WSVSCf2mtGD3spscXx/GyE/aYmj67DENjuYGvNuvOcuORnFRo6DXL2ewmTsIQRC5nVxAE11dLBy9kCcUUbAnFnVBFcadHDHt745Er/EaMhd2xKBUqOk5pnnj0+X/izHMexhppWn8EvYLzibOTPGbUms7HSsDbN9uRe5GCfn5H2GVsRRh90ScBy8hLX0r6ek78PCYBc0H4X74MwDSM1N55Z3W7Fl+nZDmU9CbMx/f7b/UKPY7KsiFvDI5y4f54WxRM9Xby9aE1S+3JCP8OjdNJSw7F8e6GylM796EsR3d0JdV/64XvoV7f0GfxdC0f6P2W6PRsHfvXpRKJSNHjkRXV3uOakQNX13/iu1R2xnVdBSfdvgUSS1Bv75dHAk9lULwX/G4+lrWOFemu9hwPDGVv4P6cPFeBN1b+XG3tILf0vOY4GSNhxjHLY0cC/P6JV3qRUmmVqOtKFVLRp+xZuM/URkWTuZnnyGPisK4T2/sP/uMwKLzLLm6hO2R2xnjO6bBPqTGRjgsXIhp//5kfrqA5DFjsRw3Fpt33yUvR0lOcildX2v6+GTA1ge6z4WzS7Xls5oPeqZ9MdLTYdlQP3o3t+G9CzeJtgzjy4Pn+dXDE3OzhieOUmNdTLo82yQt9HQK2/8aiZG7HzNKv2ah3if08JxL0EvTsdDTrUHyUItoFCryf91E+ZVrJAf14phJUyqrVJhIJfjZm+LnYIKbmSESjfg4UVSL6Cg1uBYrSSqooqW9ITJBgtTaHUVCBPKEYkR1NZlUadCo1ORTis5pKQ5tPTHv6/7kCQ+1wMXSkN1vd2TlyRjWnY/HztKAkOYmrLXOYZZbzZAEA2MdBAlkxRfTYYgnrfu5PRcZjKfFxcIypAJ0NDfG1FrKq++25uAPIaSe/RgJn9Oh22pMTWuX4JEnJFBy/Dilx08gj9HG+Rm0bo3dJ/Mw6devBgEz7tmL9PffJ2XyFKymTMHmndkIssZVLvgn1OVKpI2sevCvwHPNyhQEYRFQBkzlv9yVeR/5ChWv34knqryK9S3cGGjTOOvRsyA3pZS939zCzt2Uwe8GNKjV0xgo1RpeXn2RkvwCtqissGtZgklHI1r/kk1fDwPm27egPDgTqZU+lsO90fN8sv1MCM3l2Low2g/2JGig+zOP978FGlHDvIvzOJZ4jG+6fcMAj7prqGoqlOT9fg9Z+i4sZGsgcBwhLiWUlcfQudMFJBIZbOzP6gx/rJsEMHr0aPLTy9j31Q10ijLpKrtEk/WrEXQaN58qPpFE6blU7D8IIrxSzsqT0VyMzcPWRI9Zvbx4w+QOsj3joNVrWmX/RsYDnjt3jnPnzjFkyJAHlhO1Rs3i4MX8FfcX433H80HQB/W6u2JvZHNy4z36TPSlWfuaWbtpxSV0uxyGtY6Es73bMSIknjS5gkvtmlOQvp6EhFV063oTmewpJkhFqdoyQOW5MHpXo+VAGgNNRQW5P6ymYOtWdKyssPtsAab9tJY4URSZfWY2wRnB7Hh5B94WjZeQ0ZSXk7NyFYXbtyNzcyWh/wISk9RM+KoLega1nAtqJWzoAeV52izNOjTBnhQhmdGMP/EaiuJWOJSOYMuMPrhYvjjtJ41G5NidDJbuuEuGoMHWRI/Z7Yx5I+1LdJIvas/bQSu1RdKrEZ1VQsJni3G/eJQ/mvVlV8uX6NnchsH+TvT2sX04IWkAuaml7Fp6g07DvGjdz5Xs5csp3LmLZjeuoxYEkpKSiIyMJDo6mrIybZypRBQwFQyxsbHBvqkzNna2WFtbY21t/WDy8jS4GJvLeztDKahUom5uxomhgTQ3NkCj1nDzaBI3jyahZyijqlzJyE+Cnp8m5lNi4K0YpAgcavPwHM9NLeXA97fRaArx6LOezj3XYmjoDtRBxgIDMR3QX0vG7OvO6tdUVpK9bDlFu3dj4O+P48qV6Do3fiKgLlNQeiaVsuuZ2M5s/ZhA+vNGY12Zz0TMBEEwAiSiKJZWf/4b+ALoDeSLorhCEIR5gKUoinMFQRgEzAIGog30Xy2KYrvq4P9bwP0szdtAG1EU64y2/FcQs2y5kpGh8aRUydnY0oPeVv+6Ez76WhanfougVS9nuo5q+lz6vJlUwIh1wUzQLWGKwoFS2128lDOITwyMGVQleWgla6z+UDXklSr+XHQVfWNdRs4Pei5E8r8JCrWCqSenEp4Xzi/9fiHQLrDOthqFmvxtkeglrMZUZyfl7d7gqv7ftGjxPfZ2r8Dl1Rz6+xzhum2Y+/E8pFIp6dGFHPz+NiaF8fQKKMFx3ocNjkkjV5O54jr6nmZYjX2oK3YtIZ+VJ2MoSQ5ln94iKs29MZt+Eh29xj1gExMT2bx5M/7+/gwdOhQApUbJpxc/5VjSMab7T2e6//QGY5DuSx/Iy1W8ubjDY4XtF6/5ibW+XWhupE9UeRVrfFwZbm9JSMh4FIpc2rc/2qjx1kBBImweDFXFMGYvuLRteJ1GQiuBsQhlRgbmr72G7QfvIzWteb/Iq8xj+MHh2BjYsH3QdnSlT/awLr92nZTPvuCc2yxcTQt5acmrdYtiZoTAL70h4A2te/M5YfXt1fwS9gvy5ClIld588aofI9o8XwkGpVrDoTsZrD0XT2xOGWZqgbe7ezKxv7eWWGnUcHElnFsOlp5k9VvLvkxLDoak0/n0n4yIO8/VtgMweuc9+rd0wMzg6Swh+1fdpjivkrFLOlJ09AjZH80lYfp07laUI5fLkclkeHt706xZM22yWHImWVEp5JcXUSqprOHyMTMzw8bGBmtr6xrvho0UNc0tlTN7ZwhX4/IxcTLmyJDW3NwRS2Z8Mc062NP+VU/+XHQND39r+k5q8VT7+zxQpFTheymcd93tmOtR072Yn17G/u9uolIV0bT1ZnyKO1Hx90XksdqEt8aSsdpQcuwYmZ8vBMBhyReYDqh7ggza+3DZpXRKz6chKtUYBdlj2tcN6XPWd/sn/lXEzBP4q/pfHWC7KIpLBUGwAnYBrkAKMFIUxQJBe/X+BAwAKoCJoijel9iYBNyvkrxUFMXf6tv2iyZmaVUKRobGka1QscXPgy4WJg2v9JxxcVcMd8+k1WpVeFrM3XOHfbfT2YyCexpdliHyp7kVga/7oOf+dAK3Z/+IIvJSBiPm/ftna/8uFFUVMebYGIrkRfwx8A/cTOsWSBVVGgp2RqEftQAj6WniWrhS5NGMoKA9UJBA2OrX2Msgpk6dilN1mvd9C5NNzm36TWiG+eD6A9VLL6VTfDgBmxn+6LnW/E3Eslzka7tTXlnFgIovMLJy4r2+TXm5lSPSelwgZWVlrFu3Dn19faZOnYqenh5ytZwPz3/IudRzvN/mfSa2nNjoY5YaUcDB1aF0GemNf2+XGt/dPnaQz6JTueXfmc7mxuwJaIIoqrhwMRAHh+E0a7qo0dsBtIKtmweDqhLG7gfHhmOkGgNVQQHZy5ZTcvgwup6eOHyxGMOguu+751LPMfvMbIY3GYN51VAOhmaQX67Aw9oIT2sjPKyNcK9+97A2ekzA9M6JBC79lUTQzRVYWYDD0i8xaleHW/fUIrj0HYzZp60C8BxQqapkyP4hlJdUoU54m0yVKf1b2LFsqB9Wxs8W01SlVLP7ZirrLySQVlhJU1tjfNNV9PK0ZvBM/xptc0vl3Dp/iLa352KsLmGJagz2qTJ6Xz+M/ohRuC9Z9MxkMfJ6Gmc2xWDsW0Re5k0G/vUXYe3boTt0KD4+Pnh6ej4mDwNQGV1AwaFYCvILKHOASk8dCqqKycvLIy8vD5XqobSFoaHhY2TN2toaMzOzx8av0Yi8d/weUafT6F8hw1BXSq83m9O0Okv14q4Yws+lM3Zpp39bfNnR3CImhSexv7UXHcxrZoLK4+JI3X+Ws9F2iGoNre+sxrqZHWYDBmLSvx8yu2eTVlKkpZPxwQdU3rmD+ciR2M3/5LGkGVEtUnErm+K/k9GUKtD3tcJsgDsy2xev+g//ImL278SLJmbvR6VwOLeIP1o1oa3ZizVv1gW1WsPB70PJTiph+EdtsHF9dnJYUK6g18pzeBtLsc9VcE4iEvJZP3TqkcCoD+kxhexfFUJAHxc6j/jvVvh/VqSUpDDm6BhMdE3YNnAbFvp1u9pEjUjR/igMQqajJw3lTksTPPsdwdS0FaU/9mBlfg/69OlDly5dHqwTcjyBK/uTcMm8QJ8vR2Do17L2vtUiWd/cQGquh+3bNR9oqBTaoPeM24gTjnKqxJmVJ6OJyiqlqZ0x7/dtSv8W9rU8FDT88ccfJCcnM2XKFOzt7alUVTLnzByCM4P5tP2nvN789Sc+Zge+DyEvrYyxSzqi+4hbrigrk/XvvU3BxPeY3a0Tzvq6FBeHcPPWCFq2/Ak725cav5HsCO0+I8K4A1ptsGeEKIoU7z9AzooVqCsqsJ46Fau330JSj8uqsFzB4bBM1oWvoFjnMpUpU2nv0BYPayOS8stJaLWlWgAAIABJREFUzC0no7iqxjp2pnrVJM0YDytDhONZGBjq8EofyF34OcqUFCzefBPb999DYvSP+5SySlsgXCWHGcGg93wkE86nnmfWmVm0LPDDVv91jqXJMDWQ8fUIP3o1f/KHa2mVkm1XU9h4KZG8MjmBrubM7OmFQWQpIX+n8Nqn7bB2NqakSsmJ8CwO3sngclweGhHa22r4WmctbgWXKUnRp9x+LPZffv2gruWToqSkhKioKCIjI0lKTMIiNwhBpqZJPx08lq/AJKgNzt9912A/olpD+bUsSk4lo6lUYdROa5ERDHUoLi4mNzf3AVG7/7my8qHmm0wmq0HUrK2tMTe1JOJUPtFXs0mXaThqoGRyfy9m9PRCKhEozq1k2+fBBPZ3o+OQJk+1/8+KeTFp7M4qIKqLHzKJgDwujpLjJyg9cRx5bBwIAuo2Pbhm/gpKQUHLV8/SqdfXSCTPx1IlKpXk/vgT+b/8gm4TT5xWrkK/WVNEUaQqsoDi44mocirRdTXBbKDHUxsjnhb/I2bPiAq1hpQqOc2NDBpu/AJRUaJg9/IbCILAyPlBGDyHwNId11OYty8MXamETl5W/D7x6QKpVQo1O5ZcRxRFXv+8fb0lUv6vIDQnlMknJuNr5fv/2Dvr8LgK9Pt/xpLJJJmJuzfexururpS2UIoUZxf7srC4yxdYloVdbBcrUOgCpULd3TXWxq1xTybjdu/vj2lDQ9I2Ffb7/Jae55lnJjN37tyR3Hvu+77nHL6Y8gWuF8lxFEWRjk15KI/cilxWQcXYOfQZ/Q3s/F8+3luPJiqD2+68u8vye7/N5dTBZuIbtzHu8z8j9+2uDjZmN9L6fSG+dyTjlux7/gs6DWRPfgM3fuE0MMV5Jr7xVB3vbSuirMlAv1A1T0xKYGyCfydB27dvHzt27GDmzJkMHDgQvVXPQzseIqspi1eHv8oNsTd0245LQRBE6kra+fm9TFLGhtJ3VCg2qwO7xYHdKrDln8+i9PBmzpOv4BWgouLMp5SWvsOokUecKtbeoC4blt7gzIpcvA78r34swFpZSf0rr2A4eAi3jAyCX3u1m2L2HCx2BzvzG1mVWcPuwkZsDpG4QAWmgHdxVYj8fMOqLqkAJqvDSdKanZeyJkPn3yqtnVv0rmxys5LvJhDjIeWO05sYcHIbVr9AzI89S/iEUQSrlb8Mf1cehiVTYfB9vU5y6A0e3fkoB6oPMOHMBCZOWcx7B1soqNdxy+AIXpiR1Kuooha9ha8OVPDNoQp0Zjuj4vx4aFwsQ6J9MHZY+e6FQ0Sm+SEM8WVtVi07Cxux2gXCfdyYnRbC7LRQEoI8aV26FNuq5wlI04F3BJIFX0HogEu+/jk0Nzd3krGamhoAfH19SUpKwqUjiNytjcx/ZiC2f7yMKTubuJ07e71uwWijY0cl+kN1SBRS1BMi8BgectbO4xeIoojBYOhC1M5dd3R0ILd54NmeiMzhhi2wlY+HRiAv1GOuN9M/zIO/L8wgwk/Npk9zqSlsY/FbI1BchnDrWmH44XwGt9TzfNlpOrZsxlpSChIJbgP6o54y1dmmDAygvdHIqncPYDGbyJh7kiFjX7ridICeYDh4kOqnn8ZsNqO6+zEMtiB09e3YPEGMVWFxFzEajRiNRgwGA0ajkdtuu43Aq6zaXQrXidl/ERoqOlj97kmCYzXMeiStM2D3SiEIIvP/dZCTle08PimeRydcWaXr0OoSTm6pZPZj6YQn+lzVNv03YUvFFv68589MjZrKX0b/pUdl4vnQb89EcXgGEokJ8Y6tuMpd2PDpy2TJMnjmuReQyX7ZwYqCyMa/HaSi1EKGeTfDPn+xixJJFEUaP8pCtDoI/NOArurYI5/Bpidh5OMw8eVu22F3CKzJquXvO4qoajUxIFzDY2PjCJDo+OGnZcRGxzN+xDTajO28WPAkpcZiHg58ikEuo7BbnWTKZnFgtzrOEizhl9s9PHaplAubcQ8OSxauXn8kMMqXwMHvI1M2MWLEtt59EdUn4Lu54Kp2Vsp8r66KINrttH79NU0ffYxEJiPgz0/gdfPN3aozgiBy/EwbqzNr2JBTS4fZjr+nK3PSQpjbP5TkYDU5zTks3rSYadHTeGtU71IW1n+aQ3VeG/63RlPRbqKs2VllUxbk8uDR7wk1NLM+ehjfpc4iKMjXWWnzd2du/QfEVyxDu3At6oTR12QerFZfy5yf5xBkDmKCfgL33v8HPtxdzmf7yojwUfHeTekMiOy5YlzTbuLzvWX8cKwSi11gWr8g/jgmlpQwZ/XC5hBY8XkOLdmt/NvHRq3Djp+HKzNTg5mTHtIZ+A3Q9tNP1L/4Eh4TJxD2xCIkP98PunqY9CoMfbBHQYsoitTV1XWSsaYmp3lrSEgIiYmJJCUldeaCWk12vn72ANGpfgyQn6DhzbeI3bP7sttutkYj2g1lmAvbkPkq8ZoejTLZt1ezmMc2l3F8/RkUblICB9oxSprZaxFZFZ5IbHYJ9Q2uyBCY7NVImreclhIHSRlRpA6Pw9/fH/dfV1IvF3aLcy7T3f+CAiFLcTFV6zdSvHYdUXU1IJGgGjAAz6lT8Zw0CUVg97zPjmYTK97Zi8VkZdBN5Qwc9ehFN8PhcGAymTqJ1KWujUZjN0P1c3B1dUWlUuHu7t55PXLkyG4m2dca14nZfxnOGbemT4pgxAVy0S5rfXUd3PvNcT69fQD9Qi+/nNtUqeOnt4+TODSI8Xf0nBn5e8aSU0t4/8T73NPvHh4b8Ngll2/bsQKPQ/ciSNUo7jtMwVd3sdw4jLvvvrubZ5/d5mD1yztpahYYpjlFzGN3IcqV2KwObOVahI3l2AcFYQnz7CRMysaDxBf+kVaP4eQEvoPNKp59zIHNImC3Oc4SJyeBslrsIIAgsdHmdwJEKd4t/bHITKxP/oQ2twYmF91NVNt57VQJKFxkyF1lKFykyF1kKFxlyF2kzvvPPaaQOq9dZcgVMmxWO8c3VBCW5EPa+HDn8q4yms8UsunjV/HwDUMUvYmZsxptRTKOhntJGJ5I/ODQC2fLnjkEyxaAu6+zUuZ1db6HplOnnRYY+fmdFhi/PjiXNun5ObOG1Zk1VLeZcFPImNoviLkZoYyI9es2v/dJ1if8M/uf3JtyL8HuzgQRKVIkEgkSJEgl0k5SLxqlVP1TiSZDwH+S4Hzs7LIA+nYTbkvWErplHzqNmlXTpnLAO5jGDgtywcq78s8QkPKy5GH8vDSEerkRolER4q0i3EtFqLc77i7yzm2QSqQgofP2r7dJgoTvC77ny1NfMrx+ONP6TmPsxLGcPNPBC6uLqNdauH90JA+Oj8ZN4YJCqqC0Sc+/dpeyOtNZlZqbEcoDY/oQG+CBIIicqGxjTVYNezPrmd8gpcBNwHNEILPTQxga49vt89OuW0ftU0/jPnIkYR9/5Gwjm9pgzcNQsB7ipzojtlQ+CIJAZWVlJxnTarVIJBIiIyNJTEwkMTERL6+e1av7lxeTu7uam273ovGuRYT+/e+opzqtZcwGPad3b0ftH0BM/8HILqGYNhe20r6hDHujCdcYDZqZMbiE9NxiNmgtbP8qj+qCNvpk+DP2tkSU51k63J9bzsYWLa/IRJburadSJzBQrSPZUoJU8sscm5ubW4/CA7VafeHsU8EBFfshdznkrQOLFuRuzv8jrwhErwgsBk90p5rpOFqI9UwNokRCTmwCaXNnEztzBoqA7mTsfNjtdhqqW9n0yVFsJoibXIKH/9ALEq3zW72/hlKp7CRZKlc3FG0C8kY7bhJXVG5m7DuXo3KVE/XM0/gOHYq8l8r2a43rxOy/EHu+L+TUnhom39v3/zSDUnAI/PT2cYxaK7e8PKTLzuI6nBBFkdcPv85PRT/x8rCXmR8//5LPKVg/nbgTB3FIE7AkTOBveQrGjR7JmPHdXf/NBhvLn92Kztq11T7UXYZGJmFbh51z9SiNrI75vk9hEHxYp38H0dXTSZpcZChcnQTK+beTMJ17TJTBnrytmEyN5Bn64R+qpDjgI9qFZt5I+QtDgoZ0Lit3lSKTS6+4GrPn34Xk7a/llleG4HV2EFcQHOz79zc0lBZjNBcQPimHiu0htJc6TyQkUk+UngH4R4QR0S+WgKgIvINDUevykf64yBkvtXgtqK88RUMwGmn64ENaly7tZoEBznbcuuxaVmfWkF2tRSqBEbF+3Ng/lMnJQRdt6dkEG/dtvY8TDd3jp36N9JqJDK2cxQ9pb9KuarjgcvHVIg9ucBDSCtsyJHw3TorJ9bf1tHJxuDCtahr7gvbRqmxFdLhibpiFXTsQqbIaN//duBpH0toSiUIu4YYMf/5nfD9CvdzIq+tgbVYt67JrqdWaUSqk3C71wLvZzsJXh+Dj1/NQdsfWrdT86XFUAwcS/um/kCrPc8QXRTj6GeLWF7C7enE49D4O1YDRaEQmk9GnTx8SExNJSEjoVTXp3OzWgEnheL26AO+FC/F78s9kb9vEoZXfYz6b6+ru5U3fsRNJGT8Fr8ALi7VEh4jhaB0d287Onw0KQj05sov/WXlOMzuX5mO3Ohh1UzxJI7pH/7VY7Yw5WkCwq4LVqX14d0shXx+sIFbjxqgaExNmByHztHZpjf56js3X1/cXsubnR5CkCa/KbUhPrwJdLbh4OhMxglMR26uwFBagO1lBR4EBq1YKiKj8rXhGmFBESqn1CSTCNwKzMgijix8dMm+0Eg0tDg86LGIXsmWxOCPjpA4F/vp4sLkjROyi2eSBm5tbl2rWxa5VKhUymQzB4kC/rxrd3hpEu+Cc65sQgczTBVPuKWqeeAJbdTX+jzyM7/33I5H951u914nZfyEcdoE172fSVKVj3lP/2fyz83FyyxkOrS5l6v396NP/4mdFv2fYBTsP73yYw7WH+XjCx4wIvbhnVnPzLmp33k5Kng6LZAhfCwm4BUay+MGe7TEMWguFG7IwZ57EmnUCV4mC8P6LsHi04z4nHWWAL3LRgOqn6UiMzUju2+kMie4lDh48yNatW5k4eQoHjSLfVjyLKDWQKn+ClyfPJCHo2imVDVoL3714iKhUP6bc213UcKbyC0pK3iIh/Hv0TWZqi8qpzi+nrb4Gu7kFsHYuK5UIeLkJeMcPwiciBu/gULyDQ/AODkWl8eo1edTv20/9K69gq6npYoFhtjnYltfA6swa9hQ14RBEkoPV3Ng/lNlpIQSou8fmXAiCKNBqbkUURQRRQER03kZw/i2KCILAzr9U4uYlY/ADQQii0G3ZLs83W5B+uRz5jxsRA3ww//lubAOTEQ9+iFiyA2HqW4i+sVjsduo7TNRrTTTozNRrTTTqnLf1ZhtIREBEIgEfdwX+ngr8PFzw83TB10OBj0pBm62aZQXL6KvvS6ollfBJ4YhSERGR02fkrD+ixmiRIpdbcfE+jMRrD1K5AZXUB4cpAm17KJgjGRGRxg1pkQzy8WDN2ydIm3BhMZF+zx6qHn4Et759ifjyiy6iB4vFQnFxMfn5+egK93GD/We86OB04FwkI/9EXHwCrq6Xr1jc+M8c6kq0jK3/Alt7MwfjwmirqyGiXyqjFt2Fob2VnO2bKc88gSgKRKSkkzphKrGDhiCT93zi2m3+bHwEykGBHFpTRu6eGvzCPZh8T1+8L5IocE4F+WRUEE9EB7E9r4EnV2RjMNqYr/bizee67nMMBkM34YG1sZgo3XFSyCeAVhxIOaOIp85/FJbIcfjaRFyOHkPYvx9pbS2iRIIpKoq2uGgMYe5I0eJqbqAmQE28rpJYQyXedOCCrctrmyUq9ApfzMoArKpgHOowRE04Ut8YbC7BHPixDKtexdjFbiQPHtvr70Z0CBiO1dOxvRJBb8Otny/qKVEo/LuSeodeT/0rr9Kxfj2qwYMJ+es7V60EvVxcJ2b/pTBoLfz05jFkCikLnh30H69WtTcY+eGNo0T29WXaH3p2b76OX2CwGVi8aTHV+mq+mfoNCT4JF1xWFAUOHZ5IyBkdUQVFlAmD+bd0GE8//2KPsvzzIRgMNH5yEFuTDP2mp0C04DluNEFxBcjas5Dc/jNE9y4KBaC6upolS5YQHx/P4KmDuW/bfZjsZsZpnmftERl6q53ZaSE8NjG+MwrqanFkbRnHN1b0aJKZnXM/BkMpw4ft6HK/KIo0VerIP1BKyaEc9Pp2JEILSncj0IFB24hwnj2Bq8q9k6SdT9i8Q0JxUTqrj/bWVhreepuOdes6LTCU/QdwuLyF1Sdr2HSqHr3FTrBGyZz0UOZmhF5TkvprnDndwvoPsy+7Um7MzKTuueexlpfjtWABAf/zB2TfjAc3H7h/tzMs/ALQGm2Utxgob9ZT3mSgrNnQqRw1WB2dy7nIpWgilmNxyWRS9QSio0czZMQoov3c8XV3oUlv4Wh5K0lBanYU1LHy1HHKdKeRuZ1B5VmNTeqMWHaRutDXry8Ds+egqPVi9ot9CfXvXnUyHDpE1QN/wDUujoivv0Lm6YnBYKCwsJD8/HzKyspwOByoVCoSExNJ7hNGzOkPkeatgphxcONn4HH5J5M1hW38/H4moR3biMv8maOTRjF68T3E9B/chejrWpo5tWsbubu2omtuwk2toe+YCaSMn4JPSM/Gp7YmI9oN5TSebuGEWaDDJpA2IZxhN/Tp5u/XEx7MO8PaxjY2D4inn6eKeq2Ze/55iNPtRqYlBPDXRRndo9iMrc7Ej9yfoPIQAJagATQFjaVUmUpTZSMuh4/gl5+Hd1s7ItAYEEB1eBi1kZHI/fy6VK1aPDS85OLH40qB2d4qVG5ueMgsqKzNuBrrkbSfgfZKaDt73V4JDkuXTTK49mF13WPobf5MHnqUmH6RZ1unkaAJ7/Z7FUUR8+kWtJsrsDebcIlSO5WWERe2bDqnpq5//XWkLi4Ev/UmnuOubfLHxXCdmP0Xo75My+q/nSQswZsZD6f9x+I3REHk5/ed9gaLXh6Cu9f/jVfO/2+oN9Rz68ZbkSBh2fRlBLpf+OBaVfU1RcWvM7xtIm65P7CD4YRPfJv4kWkXfA6AQ2uh7p1jeAwJxq0vtK9YiSLvU3yim2ksCoch9+E1bx4uYZcOljeZTHz66acAjL95PI/sdYbbfzbpMxJ8EmgzWPlsXxlfH6jA6hCY1z+UR8bHXbULvNVk59sXDuEX7sGcxzI67xdFB3v3DSTAfypJSRcYlD+9GnHFvTSop1Mc+BQl2VqMWisyBYTFy/ENsaNw1aFtrKWtrpa2uho6mpucba+zcPf2Qa1wRVFajspgInjceMTZC9lWB2ty6qnTmvFwlTPt7NzYkB7mnn4LbPgkh4ZyLYvfGoFMfnnCH8Fspvmjj2hZ8hXywECC75+NR+HLMPZZGPvMZW+LKIo06SxO4cHZS0FTDVnCs3ia/RhfP4T11r60iSo8XeVE+7vjIpNyorINUYSUUA2z00KYmRZMsMaNJmMT2U3ZZDVmUVJcTcre2RwP28Tx8M2EeYSRFpBGun866QHphJbpqLnvAVzCwtB89CHFdXXk5+dTWVmJKIpoNBqSkpJISkoiPDz8l/kpUYSTS535oUqNk5zFjO31e9a1NLPv+6WUZoegEKWM3v8yEUuX4jH4wgbFguDgTHYmOTu2UHriCKIgEJ6cQsqEKcQNHo78PFsVURQ5taeGAz8VIwf6K6WEJ3hfdP7sfLTanC3NABc5mwbE4yKVYtBZ+cPLu9nvYiPSV8WHt/QnJdAFCjdBznIo2Q6CDfwTIWUBpCzAIfNGt3Ur2nXrMR49CqKIa79+yMePg5Ej8QgLw93dHRcXl25V508qG3mttJbM4ckEu/bCOUAQQN9wlqSdOUvYzmBoqGZN7hw6bEFM8/4Lka6ZZ58gcY4keEWCdyR2AjCWuWFu1oBvJJ5TB6Hs69/rarilrJyaJ57Akp+P9x23E/DnP1/U6uZa4Tox+y/H6X017F5WSP+p/znPmnOvOe62RJJHXvnczu8Rha2F3LHpDiLUEXw99WvcFT1Xmex2HfsPjMDfbyLxBwpQ1B4gU7iVxEVv4HYR5Wv7pnL0e6sJenIQch8lZP8Aqx/AGjiZ+pPeGPbvB1HEffgwNPPm4TlxItIeWjqiKLJ8+XIKCwsZMX8EL2W/hFKu5IvJXxCt6doGbdJZ+OfuUr47csZpmTIogofHxxJ4Ga28XyN7RxX7fypm9qPphCc7369Ol8fRY7NITv4bwUE92HJk/wg//wHChzhjlpTqTiuO4uONlJ5sxKy34aKUEZPuT+ygQMISvREcNtrr62irq6E5P4+6bVvQatswqNywnrd/F5BgU3njHRJKXGw0/mFheAeH4R0Sgof3pZV1VwNdq5lvnz9IxlV6U5mys6l97nmspaVoBgQQGH0a2SN7romnG8Cy/GW8ffRtRrWNpo+0L979p1DRYqK82UCHyca4xABmp4UQ439horHugywaznSQ/j+enNblkN2UTWZjJs2mZvrUiPxpgzuVMVFUpiVj0zuPW/7+/p1kLCiou/9eFzSchp/uguYiGP0kjHkaZBeeAbSaTRxbs4Lj639GFBxED1hEdZEf6dkfkHjvbHzvufuCzz0f+rZWTu/eTu7OLWgbG1B6eJI8ejypE6ag8gpi59ICKnKaiejry/jbExELWujYenb+bODZ+bNLONJvbtJy56lynogK5Mmzjvt7vy9ky6EKdAGnGGvdzUzFCVwcBvAMhpT5kHITgk8C+j176Fi3Hv2ePYhWK4rICDQzZ6GeOQPX6N6NPtySXUq12cq+IVcvBGtpKOLn949g6Qhk8mwHsYGtTvLWXonQWIbYWI7U3oREch53kcqdM6XekU7ydpbAOW9HgEcg/Fo9bbXS+Nd3afv2W1yTkwh7/31cIi9sDH4tcJ2Y/Q6w67sC8vbX/kdmvfRtFr5/9TD+kZ7MeSzjNz0Y/bdiX/U+Htn5CMNDhvPB+A+QS3s+KBQWvUpNzfeMGLCRpvemE0wDrbZXcF9wC6r07t+zYLZT99ZRlAne+C5Kgurj8NV0CB8Mt68GmQJbbS3tq1ejXbkKW20tMo0G9ZzZeM2bjzLhF2+vI0eOsGnTJmJGxfBJwyd4uXrxxeQvCPO8cKWtTmvio50l/HisCplUwu1DI/nD2D74XYETvMMmsOzlwyg9FCx4ZiASqYTKqq8oLn6DEcP3oVT+6oTgxDdOb7boUXDLD+DSnfA6HAI1BW0Un2ikLLMJq8mO0l1BTH9/4jL8cD24hpaPPsIukbJ95Hw+dO+H3GFloLedUQEiMS4mLC0NtNXV0FZXi936SwtG4arE62w71Ceka3tU6X71M6BH1pZxfFMFt78+DLXf1XkqChYLzR99TMuXXyJXOgie4o3HG/suSk56C7tgZ9GGRTToGhhZPJIZk2YwfPjwXj//nFH18HmxZExyKmhFUaSmpoaje7ZRlnkavYfz82x1baVGVUOtey0BfgGkB6ST5u+srEVpoi5uT2M1wManIOs7iBwB877oJg4RBAendm3n4PLvMLS3kTB8NKNuWYy7tx9LnzuIR30+w71yCfvwQ7Aa4fiXzkpc7CRQB1/ghUEUBCpP5ZCzYzMlxw6DJBhXzSzAlWFzY0ifGNW5XxWMNjp2VqE/WItEIcVzXDieI0KRXKS1+XDeGX5ubGNj/zhS9UWYD/8bR+ZPuMvaMEncWWsbREXIdO5edCuqwjw61q+jY/MWBJ0Oma8v6mnT0MyehTIl5bL272aHQNL+XG4N8eWNuEtX5HuDxroTrPsgF4s2lEn3JBITF0DH9koMx+qRuMjwHBWIRz8BqaHqVy3Ss9U3Q2PXFcpcOxWlXQibdyT63Crq//YxEUuW4BIe3vMGXSNcJ2a/AzhsAqvfO0lLrYH5Tw/Atxdl7yuBKIps+lculXmtLHxxcKdq7jouH8sLl/P64de5Kf4mXhj6Qo87QKOxnEOHJxId/RgVa/NIbttKgERPk+Vt3GdNwWNY1wOJbm812o3lBDycjota5wywlivhvl1Ou4jzIAoChkOHaF+xAt32HWCzoUxNxWv+PAwDBvDVv/+NJErCGskagj2C+XzS5xdtvZ6PqlYj/9hRzKqT1SgVMu4aEcX9o/qgUV3eHGTh4Tq2f53fOVOVk/tHdLp8Rgzf3XXBo5/Dxj87D4g3fwuKSxMXh02gMq+F4uONlGc2YreLuFi0iMYz/BwQgjbEj7n9Q7khI5TYgO7/T6IgoGtt6SRpzusa2mpr0DY2IIq/eLO5qTU9EjavwOAurawLbqtDYOlzB/EP92TmwxdvZV8OTLm51D3+MJaqRjQjEgh8f2m3XM8rQXZTNrdtvI0h0iFEnYniwQcfxMfn0v6Goiiy6q8n0bWYWPTqEKprqzptLXQ6HRJBILBdS9rMGfQdOhS5m5xTzaecLdCmLLKbstFatACoXdSk+qd2tj9T/FJQKXrYX2X/AOsfB4US5n4KcU7lc0X2SfZ8t4TmygqC4xMZe/u9hMQndj7t6Loyjm2oYHjRB6R/+xKSVfdDS/Ev6w1KgbjJzkvowB5Jr8MusP+nfE7tqUci6cCsXYOL0kTSyHGkTpiCf+QvVSpbkxHtxnLM+a3IfJRopkXj1q/nKq22sYRvt/yL2fVbiTCcAZkL9bIhnNaOYNSLD7N2wzEKl61gTHUmvsZ2JCoVnhMnoJk1C/dhw5BcoYXE/jYd87NKWZoSzWS/a+ekX1u1k03/LMPSFslATwUhCjkeQ4LxHB/eRcHaI6xG0FZ1tkh/aZeeJW+mti6Liwp3JIvXQtglOdNV4Tox+51A32Zh+VvHcFHKWPDMQFwv8yDYG5ScaGTL56cYdmMf+k/+bUu9vwe8d+I9vjr1FU8MeII7+93Z4zJZ2Xej0+URZLqHtQcKeVS5GplNoMH4Du4TBuM5IQKJRILoEKh/5xhyXzf874qDr6Y5cyHv3Q4BF28r2Nva6Fi7lvYVK9CXV7B16hQq/TvYH3yMaK8YPpuc1kFhAAAgAElEQVT0Gb5ul2+4WNqk5+/bi1mXXYunUs79o2K4a2R09wHkC0AQRJb/71FsVoFbXhrEwcND8fMdT3LyO78sdOAD2PYiJMyABV+BvPfVubzSBorfeY/o/ZupChhIZtw0vOQ+SATw8HElbkAgsQMD8I/wvKzKgcNuo72hvhtha6urwdB+3oFAIkHjH9ApQAhNTCZ20NBu6r3Sk41s/uwU0x9MJTq1l0kHvYRgsdD88FRa9tch9/Ul6I3/xXPs2Kte7ysHX+Hnkp+Z0jCFJP8kFi9efMnPsCSrnrVf7cM7yUqjthqTyYRcLicmJATfzZsJaWwi/qslF2yrCaJARUcF2Y3ZnfNqpdpSAKQSKfHe8c6K2tnKWpjH2dD15mL46U5oOIUx5S42F3pQnp2FJiCQUYvuIn7oiG7bbtBaWPrMfoKr9zI96RNcAv1g7j/BPQCKt0LxNucwvegApRf0Ge8kabETwcOf9gYj25acpvGMjr6jQhg+P5aGkjxydmyh+MgBHHY7wbEJpEycQuKw0SjO2oCYi9toX1+GvcGIS7Qar5l9cAn1AEOzc4g/ZzlUHwXgoCadjqQbmTrmDqqO15H95jfEWHKQ1FaATMap0GQ2BKSSsmAmj85MRXGVhuVvldXxUWUDBSNT8JRfGwsK0S5gOFJHWfYyjtd4YWqNYfyCeJLGX50fYSfMHb+QtHMVt5GPgee1yaS+EK4Ts98RakvaWfNeJuF9fZjxx9Subu9XCbPBxr9fOYyHt5L5Tw+46tSB63AeSJ7c8yRbz2zlb2P+xuSoyd2WaW7ZTXb2PcRHv8JX3xQxMaCNYR3rEAQNDR1voRqeiGZmDMbsJtp+LMR3cTJup5+CUyvhlu8hofdZkoIg8NOSJWxrPcQx/6NE14u8ciSM8Nk3o5kzu8fYp94gv66D97cVsTWvAW+Vgj+O7cPtQ6Nw60V0V0VuMxs+zmHIXA1axU0kJf2FkOCzXnB7/gq73oC+NzoHuWWXPhmp15pZk1VD3tpt3LBrKUHGNnLSx+H12J8YMyAGqV2kPKeZ4uMNVOW1IjhENP5uxA1ykrSrrUZbjEba62tpPY+snbtYTSZUGi9SJ0whdeI0PH2dJGzN3zNpbzBy+/8O/20EPrp6TK8Ope6wGkuzDc2cOQQ+9ywyzZVXPdrN7cz6eRb+Mn9STqcwe9ZsBgzoHo9kNpspKioiPz+fgvwiRBy4urqSkJBAYmIike7u1N11N4LRSMTSb1DGX16UltaiJbc5l6zGLLKasshtysVoNwLgq/QlPSCddP90kuVhBK39CxHGo9RbNDQOeIHkOXchv5AKur2KrW+spFSbwDy/zwl48QtQ/aoqaGqHst1OklayDfQNiKKEQuVi9tTMRKaQM/72ZGL6d61Em3Qd5O3dRc6OzbTWVOHi5kbSyLGkjJ9CYEys0//sWD26rQW4WA7g6XMIheEwEsEOAX2dEWv95vNkkRbt5s38T95JpFnO4Xm9bx/6PLgI9bSpWD3UvLYujx+OVZER4cUHCzOuSrgz9XgRLlIJa/tffVayKIqYcpvRbqnA0WLGNUZDS/9dHFzjgqk5nol39iVhyG9Lnn5LXCdmvzPk7q5m7w9FDJwRxZBZMddsvTu+yaPwSAMLnh2If/hvZwnwe4PZbuberfdS0FrAl1O+JM2/a6vKaZ0xCYXCi5xt0Qh2K/fdsRBx6Q04lAnUt7yMKiMcW70B0SESOHA3kp2vwYSXYNQTl7UtJ06c4MNdH3LS/yQZfmm8aZqKbcV6TFlZoFDgOW4cXgvm4z58+BWZMmZXtfPetiL2FDXh7+nKw+NiWTg4HNeLnF2LosjP72XSXNtC5MQnGDV2A27KMNj5Bux7F9JugTkfg/TC69Bb7Gw+Vc/qzGpO5Z3hvpy1TKg+iSkojNDXXyNw1LAen2c22CjLaqL4WAM1hU41oU+IO3EDA4gdEIhX4LVr5YuCQEVOJllbN1B20pmJ22fAEGKHTGX3Mi1DZkczcHrvvecuG5nLEFY9SIt1Ls3rjyP38SHo1VfxHH/lFgKri1fz0sGXmCJOwbfOl4ceegi1Wo1er+9sUZaXlyMIAkpXFbRpGDamPyOmZCCXy7E1NnLm9ttxtLYR8fVXuPW9eoGCQ3BQ0l5CVqOz9ZlTl4U6V0tqqQaZICE4oZ0F8iKkMgWGGX/FK+3W7ivJXQHrH6fRFMZPjW+Q4lnO6L/ec/EXFgQsFVns+aGM4kofQl1OMVHzdzw8Jc4qWtwkZ1XtPHIniiK1hfnk7NhM0aH92G1WgmJiGJYRQiRFSIs3I7EZsIt+mBiLZNAtuI0ZjmH/HrTr1qPfuxfsduqCQ0lecCPtYUPYsVHLzEfSiOz7y0nWuuxanluVCxJ4+8ZUZqReeD7uQmi32Unaf4rHzxMdXCnMpe1oN5Vjq9YjD1ShmRaNMsEZ65V/+nWOLPfF2JjI+DuSSBr+/6f47Dox+51BFEV2fltAwcE6pv8xheg0/6teZ1VeK2s/yPqPKj9/T2g1t3Lbxtsw2Ax8N+07wtVdB0+rqr6hqPg1aJrH/nwlT987H2VHOeLyxdh9x9FQ8z+ADL+RlSiPP+RUWt34+QXz7HpCQ0MDT33/FCe9TzIseBj/GP8P3OTOWS1LSQntK1aiXbMGR1sb8uBgvObORXPjjbiE9ezJdDEcq2jl3S2FHClvJUSj5NEJccwbEHbBVkp9mZaV7xwHiUBQjDcRLlmEN3xKwODhSGe/301lBc68z30lzaw+WcPWvHrMVgc3tZ3i1hOrcLGY8Lv/fnwfuL9HRWpPMHZYKT3ZSPHxBupKnHNM/hGexA4MIHZAAGrfqxvIPx/axgZytm8id+dWbPZ05Mr+DJhiIn3yuGsiJOgRogjfzYPKw5gmLKXurY+wFBainj2LoOeeQ3aBmKKLQRAFFm9aTLm2nHHl44jwj0AqlVJVVQWAt7c3SUlJxMcnsG9JDQqFjJufH4xEKsHe2sqZO+7AVltHxJdfoMrIuMSrXebbFQTyD+xh//dL0bU0oe7bh45h/uTYi2mry+TN+jr6Wa2s9g3iaL+Z9AvqT7o6lvhDn6E4tQLCBsONn/H9M4cwiiru+tfsi3YR6kq1bPvyNPp2C0NmR5Mx0hNp+a5f2p6mVpBIneuNm+RsewalOP+HRRFLyX60Oz7As24vbhIzZoecJo90VCPvxTNmOs2fbcRwYDv2upNgMyP390c9YwaFo8dxk1nBo5GBPB0ZxNLnD+Ib6sHsR9O7bF9Vq5FHvs8kq6qdWwZH8NLM5F5VtM9hQ1M795yqYE1GLEO8ruw3aqs3oN1cgbmgFZnGBfWkKFT9A7p0fkTRQVbmn8haE4exoS9jb02g76jL3wf9X+M6Mfsdwm5zsPrdk7Q1GFnwzMCLOkZfCjaLg+9fO4JMLuXmFwYhV/zn4yt+D6jQVnDbptvwdvXmu+nfoXH9pY3ktM4YiVKezuZt0SxKcSV+3rNw5FPY9BTWiEUYhOl4Nf4BiV8c3LWpVwPw52CxWHjo64c4ojzC6ODRvD/hfVxk3YdqBasV/c6dtK9YieHAAQDchw3Da8F8PCZMuCz/H1EUOVDSwrtbC8mqaifSV8VjE+OYnRbazRPMZutg54a7sDZPxlzsT6NWDUhxcZMTluhNeJIP4Uk+qP2UnKrpYFVmNeuya2nWW/FSKVgYKmXmjqXITh7DLT2d4NdfwzXuytst+jYzJScaKT7eSGOFM4YnKEZN7MBAYgcEXDi38zJh1pv45rlDSKhD1/A9cldXkkeOI23ydAKirl01vBPtlfDJMAgbhHjzjzR/9jnNn36KzMuL4FdexnPixMteZWFrITevv5mR6pH4ZfkRGBhIUlISiYmJBAYGIpFIyNtfy67vCjpPJB1aLWfuvAtrWRnhn32G+5DB1/RtVuefYvfSL2koKyYgug9jb7+H8L6pnY/bHDYKmnKQ7Xyd5KJdFClVPOanoUqhwE0Q6OsWTHrsDNID+6P8qpDjtbFMviOWuOHd554Eh8CJzWc4tr4cT18lk+7pS1C05tcLQW3mWZK21XkbQOXnVIrqG5wXmSti/BTa/EdwvMBA9Y4dBDW0Eqoz4WKxInFToYgYgMx3AG4DB+M9Jw6XUA/+VFDJj3WtbBgQj2N/I0fWlrHwxcH4hnYlUDaHwN+2FvGvPaXEBXjw0aL+vTZMfqqwipUNbRSMTEFxme12u9ZCx9YzGE82IHGV4Tk2HM8RIUgucKxxOCycPHEvpzcNwlDXj9EL40kZe21UoP8pXCdmv1PoWs389NYxlO4K5j89EBe3K1Ta/FRM9o4q5j6RQUic9zXeyus4HycaTnDf1vtI8Uvh88mfdyFHhUWvUVPzb44enEWGSwtTnlzifGDri3DwA3BVg0IF9++6rExIURR59IdH2W3dzSj/Ufxj6j9QSC89q2WrqaF99c+0r1qJvbYOmZcXmjmz0cybd1lzQKIosquwkXe3FJFX10FsgAePT4xjZJSO1rbdtLTsRqs9gSg66GdKJ/DYdswDn6Aq6AGq8lupymtF3+a0rdAroERip9pFJKafL7P7B5NxZDOtH3+ERCbD/4nH8V64EMmFApuvANomEyUnGig+3khLtR4kEBrvReyAQPr098ftUqqxi+CcKnXOY+koXFrJ2rqRggN7sFsthCQkkz5lBvFDhl8w6ueKcE7hOvsj6H875vx8ap99DktBAeoZMwh84Xnk3pe3H3jn2Dt8l/cdX074kkFhXc1Y7TYHy146jLuXK/OeGoBgMFJ5z91Y8vIJ++QTPEaNvGZvra2uhr3Lvqbk2CE8fHwZdctikkaOvfjvIW8t4qp7Ee0WctR+bE6bTZapjoLWAhyig/QSkbGVL2HyFwm6X8a48HGdQhldq5ltS05TV6IlfkggYxYmXHo/rG+Ek99A5nfQVvHL/RIphA3B6juCjmIR7c7DWMvLEWUy2v19KHeV0urnTdzw0fQLG4M0x4pgtKHqH4hkYjgT8stwl0lZlxTNj88fJm5wIONv71kUtK+4iT/9mI3ObOPFmcncOiTiksKNYYfziFUp+Ta19ycMgsmObk8Vuv21IIp4DAvBc1w4sl6k2NhsHRw/divFOyaiq0lh5II40ib8thYX1xLXidnvGDWFbaz5RxZRKb5MeyDlssUADeUdrHznOMmjQhm76MIRQtdx7bCxbCNP73ua6dHTeXvU2507xHPWGdqGdBoLA/jDY8+BV7jTOXv1A5C/Du5cf1kyb1EUeXrT02xq2sRQ96H868Z/IbvIrFaP63A4MBw8RPvKleh2nLXdSEvFa/581NOmI/PoXbXWZjOyI3sTuWWbiHTPwtfNqV708EjCzyURv7JSNDk7YcwzMPYZOix2NuXWsepENUWl7UTZpaQrlPgZRbA7cx011jq8ak4SGuNO0vN/xDX06mZfLoW2egPFxxspPtZAe4MRiVRCeJI3sQMCiUn3u2yl9Mp3jmM22Fn0ypDO34FZr+f0nu1kbd1Ae30dKo0XKeOnkDpxCmq/a+BhKAjwzUyoPwUPHQF1MKLNRvNnn9H8r0+RqdUEvfxSlwD3S0Fv1TPn5zmoXdXc3e9uYrxiiFZHo1KoOo2E5zyWTkikG1X33Y8xM5OwD/6B54QJV/9+AJNex+GVP5C1ZQMyuZzBc+YzYOYNKFwvYYDcXAwr74W6LHD3B0MTDLgTpr6NSQKnm0+TW36Y0BfzKI6dz8qUv9GhaWB2n9lMcszj9KoWBEFkzC0JFx9Ut+ihYAPkLofSXU4lZ1AKpNwEyXOwVxbQsWIpHftzMNU5Y8VUwaAe0Rf1DQuRpU6jobqOnB2byd+/B5vZREBYHwZHz8C9VoVELiFrXCD3oOehiABGHe6g4FA9d7w5HJW65xOHJp2FJ37KZm9RE9P6BfH2jakXtLupNFkYfDif12NDuS/80qMzol1Af6gO3a5KBKMdVbo/6slRTkPsy4DZUs+xIwup2HcjHVX9GH5jLBmTr5Fa8zfGdWL2O8e5Hd/lDg877ALL3zyGxWhn0ctDrrjidh2Xj89zPueDzA+4P/V+Hsl4pPP+rOx7aGk+zv79s3hyXAiq0Q86HxBFsHQ4zS17CUEUeGH3C6yrXEeGmMGS25cgv0qDUXtrK9o1a2lfuQJrSSkSlQr19Gl4zZuHW3p6t7Nuk6ma5pZdtLTsoq3tMIJgQSpV4RATqCmFoLomRgrFuIsGRCQ4xr3Ibv/bWJ1Zw7b8Bqx2gRg/d+ZmOP3Gwn1U2HR6Ct9bypnDFbT596VDFYaIBBeljNCEs23PZB80/m6/mTmyKIq01OgpPtZIyYkGOprNSOUSIvv6EjcwkKhUPxSuFyfAzdU6fnzjGCPmx5I+sfvBRhQEzuRmOcUCJ44BEDNgMOlTZhDZL+3qqoItpfDP4c5h9IX/7pxVNBcWUvfsc5jz8lBPn0bgCy8g74U/GcCuyl08ufdJLOflIgargnFt8CFUEc7EUQPx+GwlvrtPEf+/f0UzY8aVb/9ZOOw2srZs4PDKH7AYjfQbP4kRN92Gu9clKn6iCMeXwJbnnf5msz+E+Kmw603Y/x4EJMOCr8HfebJaOOtGdoc8gF+GhtykrbTuUJDQOASTTysj74hmaGJ3NSoOm5OE5S53kjKbETQRzvnQ1JsQPCLR7diJdv06DAcOgt2Oa1wc6kmj0cQrULQfdSo+rXqQuUDUSIibjDV8DIWF1eTs2Ex9SRFqpT/Do29AY/bhzQwVPwfIWBYZRt47OQyeFc2gGRc+JgiCyBf7y3hncyGBaiX/WJjOwKju3/ey2haeKKxiz+BEEtwvTK5EQcSU0+RUWrZZcI3zQjM12mn3cYUwGEo5dmwhNYcW034mmaE3xDBgatQVr8/msKHohbr7anGdmP3OIYoi27/Oo+hoAzMeTCUqpXc+SMc2lHN0Xflv4p10HReHKIq8cugVVhWv4rXhrzE3bi4ALS17yMq+m4KCEYwXBZIe+u6K1m8X7Ly4/0XWl6+nr6Evn976KZqrsEboaftNWVm0r1xJx8ZNiEYjLrF90MybC+MjaLMdp6VlDwaD05DTzTUMP0kEvi0WvEtykWprAdC7hbLDksxWcxIdQUM51a6gzWjD192FWWkhzM0IJTVM00mw9PsPUP/KK9iqq/G66SYC/vwENpkb1QVtVBU42566FjMAnr5KwpN9CE/0ISzRG2Uv2idX+lk0VugoPt5AyfEGDForcoWUqFQ/4gYGEtHPp8e5zd3/LqTgYB13/mXEJbeto6mR7LNiAVOHFu/gUNImTafv2AlXLhY45w8370snWTj3fmw2Wr78kqaPP0Hm6UnQSy+hnjqlV6u0OWxU6iop05ZR2l7K8fxcSlpL0Xk2YRWsncv5ufkRo4lxXryc1328+uCr7F3slSiKFB89yL5lX9PeUEdUWn9G33Y3/hFRl95IfROsfQSKNjmJ6ZxPurr4l2yHVQ84idSMv0H6ImpfeIETea5UB43E00+JtsmEkN7Ijx4fo7W3kxGQwZ1972Rs2BikNSch50en55ixGdy8IfkGSL0ZMXgAhiNH0K5bh277DkSjEXlQEJqZM1DPmoUy4VddC7vV6ZV2TkDQXOi83ycG4ibT6JFObmEL+Qf2oRF8SQydyn0jw1BKJbycL1JXa+CON4dfcm44u6qdR77PpKbdxK1DIhgU5UNKqIYIHxVSqYQHTldwuF1P1vC+F/x+zMVtaDdXYKvRowh2dyot46/NaIxWe5ITJxbTcOKPtJYmXpJw9oRybTnLC5ezrmwd38/4nnDP687/V4XrxOzSsFkdrPrrCTqazSx4duAlHftb6wz8+L9HiUn3Z8q9/f5DW3kd58Mm2Hhw+4Mcrz/OJxM/YVjIsE7rjKZGHYrMEKY/taS7d9Kl1uuw8cy+Z9h6ZivJbcm8MeMN4q5iEP5SMLVVUrPvE5obtmMMbkNUAYIEtT2MQIkPfpVVqGqKnAu7eUP0GGewdMxY8InGYnfww9Eqlh05Q3ygJzf2D2VUnH8XBae9rY2Gt96iY+06XKKiCH79NVSDugdLi6KItslEVV4rVfmtVBe2YTM7kEggIErdKSIIjFEj+w18+kRBpK5US/HxBkpPNmLS2VAoZcSk+RM7MIDwRB9kCilWs52vnz5ATIY/E+9M7vX67TYbxYf3k7V1I7VF+chdXEkaOYb0KTMvXyzgsMOXk5zGmw8dBfeuJ2fmwiLqnnsO8+nTeE6dStCLL1yWz51Zb+PbFw4SGu9F36KvKD+8Bf3DC2lKj6BMW0ZZexll2jL0Nn3nczxdPOmj6dNJ1s4Rt2D34M74pbqSQvZ8+yU1BXn4hkUw5vZ7iE7voWLVE4q2wpoHnaajk16FwQ/0qPhFV+9scVbsg9SFtFvHUPr2Pzky7FXcvVyZeFcyofHeGG1GVpesZufJTxnUVM5so5UQqxlRrkSSMA1SbkLsMwFzXgHadevp2LQJR0sLUrUa9ZQpqGfNRDVwYO+rn20VToJWvA3K94LdBHI3bBGjKXIkklPUTrmsDx9MGMPt5VZuyGnCZ1ZfkiZEXXLVOrONl9eeZl12LTaHkyt4uspJDlFzAhv9QjX8dVAMMf4eXcQ71lo92k3lWIrbkXm5op4ShSrN/5p6bAI0N+8kO/uPtGT/maaiPgycHsXgWdEXJfJ2wc7uqt38WPgjh+sOI5fKmRQxiYcyHiJSfT0r86pwnZj1Dh3NJpa/dQx3jXPI1kXZc9tKFERWvXuStgYDi14eesEZhOv47aGz6rhj0x3UG+pZOm0pcd5xVFUvpajoVc5kDuPu8dMgowefpQvA4rDw+O7H2Vu9l9SWVO5KvYuJV6C0uxhEUUCnO0Vzy25amnfRocsFRFxkXnh1eKE81IxjuwmxQ4bc3YFX/wC8Zk5BMWgWBKX2fCC84GuJdKxdS8Nbb+MwGPC77158H3ig1xYYDodAY3kHlfmtVOe30lDegSiCwvW8tmeSN16Bqmve9hQcAjVF7RQfb6AsswmL0Q4S8PByRSaXom0ykTQimNA4Lzz93FD7uuGucen1Aa2xooysrRvI378bu8VCcHwi6ZNnED905IVNU3+Nhjz4dDQkz4b5S7o9LNrttHy5hOaPPkLq4UHQSy/iOXVqrz6rg6tKyNxWyQT3g4jrlxHw1FP43n1X1/WLIo3GRidRO4+slWnLaDW3di7nJncjQhWGqtmBpLyVAMGLCWMWMH7izbgoevFbsBqd1cFjXzgNWud9fulQd8EBe9+FPW9jIZqy700on3mL4AUznBVOXYPT5Dl3OdRmIkok5Hr4sNxV5IRPKLd4z2RcvgzLlu3YzlQicXHBY+xY1LNm4jFmzGUpnHuEzQQVB85W07Z0Cgma3ZJ5LOwhdgT35bMjOlLa7BgizUTeNAQP/0sTa6tdoKhBx+laLadqOjha2UZBfQeSswlkbgoZySFqkn3diWm2ElVpIEbpgs/4CDyGhVw04/NqUVu7nLz859CefoH6vAj6T4lg6A19uv0em4xNrChewYqiFTQaGwlyD2JB/AJujLsRP7f/THfoOjG7jk5U5bey7oMsYjL8mXJfvx53oDm7qtn3YxET7kwicehvOyx9HZdGnb6ORRsXoZAqWDZ9Gd4ubuzZO4TGhmBm2YPxuP3bXq3HaDPy6M5HOVp/lIFtAxnhOYI777wT2RUYxf4adruOltb9tLQ4VZRWazMgQS0Jwq9Dgm95OZ7tOiRIICQDIXwU+gYN7XtOYTh8BAD3ESPwmj8fz/HjkPTioGStqqL+lVcxHDhwTSwwACxGGzWF7VTmt1KV10JHs7Pt6eHjSkSSD2FJztan0uPatj0ddoGq/FYaz+jQNhkpy2xCsIsIQtd9skwuxdNXidpPifosWeu87afsUVxgNujJ27ODrK0baaurwU2tIWX8ZNImTkPt3wuxwO6/wO43YeH3kDi9x0UsxcXUPvc85txcPCdPJuilF5H7XfgAZ2i38N2LhwiW1RG3+TX8Hn0E/wcfvPS2nIc2cxtl2jKKmgo4nLmVwsZ82t1tGNzsncvIpXKi1FFEa6I726ExmhiiNFG4ys4StrpsWHmfsw047GEY/6Jzrqy3KN+HuOJeir4F9bBUgv94o7NVWb4HRAGC05xD/P3mYTPLOPXjp7SvX0fQGR0C0JIcRPi8W4mYddM1ySntEaLonBs8a8ehrz7J2PTPcDhc+fvOOvq4hmOwa2n0riVsen8i0zKQ9lIE9HFlI68X17AyLpL6JiO5lW3k5DeR32HCdHYZF5mUxGBP+oZoSAnV0C9UTXygJ8rfwHqpvOJjSkvfx1D0OtXZgaRNDGfEvFgAjtUf48fCH9lZuRO7aGdEyAhuTriZUWGjkP+/9u47Puoq3//466TMTHrvtEBICC0BAekdQUBRUcSOimXd6xbdu151i/vbXd297t617epaFnuh6SoWkCauFAUpKRBKElImJJlJZibJlGRmzu+P7xAIhBAgCYmc5+ORR6Z8kznwzXfyzimf49e1c6hVMFNa2L2uhK2rDzPu2gGMnN2yu7auxsl7v9tB4oAIrnowq9MmRyvnJt+cz5IvlpAakcqy2cs4kPM7zDWrif8umqyHN4Ku7ZWPdY11PLD+AfaZ9jHdNZ3EmkTuv//+855XJqXEbi/UJu6bNmGx7kRKNwHCQLQrnFhjNTEVJnRNEqIHnBia7DfxtKHXxrJyrKtXY/nwQ9wVFfhHRRGxYAGR1y9En5Z2+mu73dS88SbVzz+vlcB46OdE3XRTh5bAOM5abad0f6027HmglkaH1qsV3yeseRFBYv8I/AM67rW1Yrq7mHJzBpnjkqircWI1OagzObCZnNhMDmxm7bPL7m7xtfrgAF9gOxHWwmKDiIgNIjRSR3lBLnvWreHITm0vxf6XjSZ71lz6Dh9x5v8/dyO8PBXsZm2VZlDrhWal24152TJMzz2PX0gICb/+FeFz57b6HvLVuwXkbSll7PYn6PwV01wAACAASURBVHXbdcQ99PNzfq/xejzkbFzLN8vfwWGzkjlpGhMX345/RDBF1iKOWI606Gkrqy/D69tY3k/4kRKawgCPILUin/5+BgZMfITUwdcTqjuPOXn11ZQsnktTVS0D5lZDZF8YvgiGLcITlELd+i+xfbKGhm3bwOtFn5lJ04yxrOh7jFWWTXill1l9Z3HnkDsZEnvhuxuclaue/xTs4HpzDBMOWrk/bzf99Qno/XthcpZxsGkHvaeOZuiM2YRFt92DtHjPEYyuJr4amU79ViO2TaVIlxtDdhw1o+LYX+ckz2gjt9xKbrkVm1P7mQ3wEwxMCGNocjhDfWEtMymcYN2FBSQpJQUHn6Cs7G1chX+leFc4uqwG1iS+SqGtkHBdONemXcuijEX0Cb94KzhVMFNakFKy7rU8juyqYv6DWfQZHNP8+JoX9mE8bOGmX48hPLbjKpkrF+6r0q/4yaafMDllMr8f8xN2fjsHd0k8cy5/VBtqOoNaZy33fXkfhyyHWBy6GMdeBzfddBMZp04kPguPx4XFst0Xxr7C4SwBIMQbTqzZRUx5JRE2N34hcVoIS50C/adAZPve/LSyG1uxrFhJ3caN4HYTlJ1N5A3XEz5nDn4hITjy8jj269/gzM8ndPp0En/zawITu2a/PK/HS9XRuubaaceKbEivJEDvT0p6JL0HaUEtKvHChj3Xv55P4e5qlvx5whmnGxznsjedCGsmJzazo/l2ndmJx+09cbCAkAg94bEGDCEu6k07qSzcRqO9jvC4REbMnsfQabMwhLYSTIy74ZUZkO3b/qqtNh0+jPHxx3Hu3UfYrJkk/uY3BMSdKKFgrXbwzq+3klz+NWPH6kh47NFz+v+SUlK0Zydb3l6GuayEXplDmXLb3SQOaLu31OVxUWwt1kJb5W4KD3xEYZOFYp0eNyd+9yUEJzT3rp3c0xZlaHuiuukf/6D6uedJX/13/NImUv/NN9g++YS6jZuQTieBKSmEz59PxFXzW/zBcazhGO/uf5cVB1dQ31TP6MTRLBmyhEkpkzr9D+P/OVjGG2Umbt9o45Fx+QQUlGCtHI8QERTV5ZBbu4Wk/pEMu3IhqeOmn9aL5vR4GfSfHBYHBPHTLRY8Vhf69CgirkxFl3T6H4tSSspqHeSWW8kpt5LrC2w1DdrCDz8BA+JCGZoSwRBfYBucHE644dx6qKX0sPX7O3FYvuHrHbcQXzKVir77GXV9L+akzsYQcG5lOTqDCmbKaZpcHlb9707qa13c8OhoIuKCKNhxjPXL8ntcob5LyXsH3uPJHU9y06CbGG7aQqB/CbPsE/C77pVWjzc5TNyz7h5KbCU8NOAhDq07xLhx45g9u32r6JxOozZXzLyZmpqteL0O/KQ/0XYdMRUmYswugrxB0G/CiV6x+MHntBVUa9xms1Z2Y+VKGgsL8QsOJnj0aOr/8x/8o6NIfPxXhM2+4qL26LocbsoLainbX0PJ/hqsVdrATWiUnl6Z0drQ56AogsLaP1fIWd/E6//zDZnjk5hygXUDpVfSYG3EZtZ626wmp9br5uttq7e4kF4P3qZDuF17ke5yEAGExw8nZdAUEtPSiIgNIjw2iLAYA4atf4BvnoHbPtRWK7b12h4PNa+/TvWzz+EXFETCrx4nfP58hBCsefQjSk0GZsftJPWPj5/TOawqLuSrt/9FSc4eIhOTmHzrXaSNGntuPwe+fS6RHrjyf3EPX0RZfTlHrEcoshZRaClsvu1wO5q/LEofddqig/4R/UkI1nYvaNi+nZIldxIyeRLOfTl4LBb8IyMJu3IOEVddRdCIEW22s66xjlUHV/HW/reosleRFpnGHUPuYF7qvE4r39Dg9jB1xwEaapz8X10wc27OxGupoW7NTurydHi9Hg5at5Jr2UWQrpGhQ/uQOfMaorJmgp8/m3IquNlcxd++tzNdF6SttEw7t627pJQcsznJLddCWp5RC22VthNlVfrFBPt61SIYmqyFtqiQ068rl8fFuuJ1LC9YTm71bh6Ib6KvzktDyV8x7ghl8IQkpt4yqMMXHpwPFcyUVlmr7ax4aiehUQbm/mgYK57aSUR8ENf992X4dYMfXKV1T3/3NG/mv8n1MROZGLyO1MN+9L87H0558z7WcIyl65ZSZa/iydFP8t2q74iNjeXOO+8kIKD1nhiv143Ntqd5iLK+QVt+b3DriK1uIMZkJ8rmxT951IkgljIKAjpngYiUEsfuPVhWrqR+82bCZswg/hcP49+BpT06is3k0HrTfMOex4cZ444Pe2ZGkTQgEv82Jj/vWV/CNysPc+OvxhDbq5P2xPTxNHmpqzkxNFpx6DCleV9hqdiN9DYh/BMJ0Gfjp0tHiAD0Qf6EyRLCA0yEj5lNeHz4ieHSGEOrJRdchYVUPPoYjr17CZ0+HdeAbNYeTCVNX8wVf7sT0c75jfW1NXzzwVvkbl6PISSUcQsXk3XF3HPb8cBphc/+W5v/1Ws0XPeyVlbiDLzSy7GGY82lPYqsRc23bY225uNCAkPoH9Gfgfre3PDw5/ghCJ42mZgF1xE6YUK75kuerMnTxBfFX7AsbxmHag8RHxTPzZk3c0PGDYTrOn4O2je1dSzcc4TLD7v44KaRzfMn3WYH1s+LcOSa8QY4KLStY1flfkCQFBRDdvwVvJWRxpv9dOyMiCdxZHKHBp4q3xBoXrm2yCDXaKWs9kRQTokMYmhKOEOTI0iMbqLAvp51pSupddXSN7wvN2bcyNy+0ziUew8OhxH/6pfJ2dDAoLGJTLs986L/jlPBTDmjo3lm1rywF50hAHejh0WPjyYmuXN/ISgXxiu9PLT5ITaWbOSWMMFYfyeTh7yISDvRi1FqK2XpuqXUNdbx3LTn2L1mNyaTifvvv5+oU7bTaWyswVyzBbNpE2bzV7g9dQgpiKjzEmuyE1PTSEhIGqL/NC2I9Z0Ahk6apPwD4fVKqo/WUbrfTOn+Wo4dseL1SgJ0fiQPjGyenxadFNLciyK9knee2E5QqI6Fv2xneYdO4LI3kPfVRvas/ZTaijJ0QaEkDhxPZMIonLWN1BWXYJNJeLwtQ1VIhI7wuNMXJIRF6XF9vBzTs8+wL+12auOGcPufJhMUefapEk1OJzvXfMh3H6/C43YzYs58xl63uPXh1rYc3arVHrOVw5RfwqRfwHkWU5ZSYnaam1eInhzavMeqaDCAUy/oF96PYbHDGBo7lGGxw8iIzmh1/9m2XmercSvL8paxo2IHIYEhLBy4kNsG30ZiSMcO3z+8u4h3LFaecoVy55yW8zpdhRYsawppMjbgnxCI3VGO3hZPo8fOTZfr8DTauPXjl4mPDSE5YxApl00neXDW2Yv4ngeLvbE5pOWUWdhZUkml9URuMeidDE4KY0L/vr5FBhFEGSx8v2sRXtmIv+mf7P6ihoGjE5i5JLPNTec7mwpmSpt2fVHM9o8KGT2vH2Ou6oSNkZUO53A7uOuLuzhgyuPBBAcL5SQi5mrlDI5YjnDPunto8jbxz1n/pHRnKdu2bWPRokUMHjwYKSX19fnaEGXVl1jrcwFJYJMg1uwgpqaRmKZoAvpNOzFXLFytzr0QjU435QctzfPTLJV2QAszvX2rPf38BetezWPmkkwyusFqaCklpXn72LP2Uw7v3I6Ukv4jRpEddYy+Ze/hWPQpNsOQFosRjs93q7e4OGnaFn4BgtAwf2y1bsbM7cPoq09f1NHitb1e8rZs5Jv336S+tob0yycw6eYlRCae4/+Lpwk2PwX/+Zs21/G6V6H36fXtOorVZSXfnE+uKZccUw45phxMDhOgrRDNiMpoDmrDYofRL6Jfc/21tuSb83k973XWFa9DIJiTOoclQ5aQEd0x2+Q1eDyM/TIHj8fL9pnDCNe37ImUXol9VyXWtcVIl4fQiSm4xycwdOcB7rTmM3vH+xiP2ah0hOCR2r8nIiKI5PRMkoddTnJGJrF9+rZ7pWdbapw1fHjoQ1YcXEF5fTnRumTGRt9AUuBojlZLcsutHKmu5/iC5pgQHYMSA4jiCwZEWxjieYBDG82kXRbPzLsGd0q9wvZQwUxpk5SS6pI64nqHdYuxd6V9TA4T16xYgEdY+aO+kenXH+CA5SD3rrsXfz9/Xpn1Cp4qD++99x6jRw9nzJhQTNXrMVdvwOWxABBW5ya2ppFYWwBh8RNO9IrFpl/wPDHlzOpqnM3DnqX7a3A1aMOe+pAAlvxpwlkrsXe1OrOJfRu+YN/6L7BbLUTom8hKsjP0kVUERZ9ecqN5mNTsaLE4wevxMvPOwW0uaijJ3cvmt16juriQxLR0ptx2N70GncdKRdNhWL1UW7gw4laY8yfQh53797kAUkoq7ZXNQS3XlEuuKRe7WwvmoYGhDIkZ0hzWhsYOJSEk4Yzfz1hv5K38t1h1aBUOt4NxSeNYMnQJ45LGXfB8y492G7m/tpJrA4J5cXLrgU82eZFeiZ/enzVVFpbmFfPxiDTGRIZCox33kS1Uffc5xvw9GE0uyu3h2D1aL6FOF0jSwAySM4eRnJ5J0sAM9MHt20dXSsne6r18UPABa4vX0uRtYnTiaG7MuJHpfaYT6NcySNob3eyvOF5rTRsKPVhp4/hamEkeHWPr/GlKMtBvfh+G9YkkNSakS4c3VTBTlB+oD7d8yB+LfktkgIfHM+/j8YL3CQkM4dUrXsXgsPHZ538mJrqM0NByJF783ZLo2kZiaz3EBA1D32+mFsSSR5730I5yYbxeialUW+0ZkxxKv268/ZnH3cShb7ex99/vUlZcRoC/IGPiDLJnzzvrqsizMZeXsuWdZRTu+pbwuHgm3nQHg8ZNOvcyKFLCrtdh7WMQoIernmtz1XJX83g9FNuKm4NajimHgzUHcUstnMcHxWtBLU4LakNihhCmaxkorS4rKw6u4J3972BymBgUPYg7htzB7H6zTwsp7SWlZNHbu/i6VwArswYwMbrtEPvLglJWV9ayf+IwAlsLNJZS5OEN2HK+xLg/h3JbAEZ7OCZXCBIBAmJ79SU5I5OUjMEkp2cSkZDYImDam+x8WvQpHxz4gILaAkICQ7h6wNXcmHEjAyIHnNO/z9nkYUfBRjZ8/zbHXJehLx/OoGNeDgV4+CSkEYNeK4w7JDmCuyak0iem7d1xLlSnBzMhRG/gTSAR8AIvSymfFUI8AdwDVPsOfUxK+Znvax4F7gY8wE+klGt9j88BngX8gVellH862+urYKZcqiorK/nTO4+wKWYnHgQpwXH8KjUTv7odOGQtAHq7JMHsIEamEJk0E7/+M6DPONCruYTK+at+4172bttFfkNfmhobSRwwkOzZ80kfN5FAXft2XgCw26xsW/kue7/8nEC9nsuvvZGRV15NwPlUvm8waftcFnym/cFxzYsQnnzu36eLuTwuDtQcaNGzdtR2tPn51IjUFvPV0qPS0fnraPQ0sqZwDa/nvU6RtYikkCRuzbyVhekLCQlsX2/UyXZtKeM2SyWGSB1fjx9MSMCZe27Hbs8nPdjAm8PbMf3F4wbj93B4A66CDRw7chijPQyjKxqjI4xGXzm+4IhIktMHoe+dwJ7AQj5p2IzNW096VDqLBy1mXuo8ggMvLDAZjcvZf+BREhOvobHip2xdcRhd72DKMkPIrawj32jj4/+awMCEzu1d7YpglgQkSSm/F0KEAbuAa4BFQL2U8i+nHD8YeA8YAyQD64F039MHgVlAGfAdcJOUMr+t11fBTLlUSSl5+umnkf2W8720c2N0I1HCi8cSSmHNYMYERZCdPQtSJ0NoO6q8K0p7OSzwj7G4AqPJT3uEPeu/oKa8FENoGEOnzSJr1lwiE848Sd3d2Mj3n3/Mjg+X0+RyMnzGHMbfcDPBEedWbqHZoS/howfAaYGZv4PL7z+n7b26G6vLSp4pr0XPmtlpBiDQL5BB0YOag9qQmCEU24p5M/9NdlXuIiwwjBsybuCWzFuID27/de9u9PD/nt7BK+OCuT0lhj9ntF426ajDxeXb9/OHgSks7RXX6jFtstdoOyMc3oD38EbM1bWUOsLZTQqVdQb0Ddp5k36CyL69SBt8mdarlpHZIYsKiopeoLDob/Ttcy+uilvZ/E4BvQdHM/f+YYgAPwR0+rBmlw9lCiH+DbwATKD1YPYogJTyKd/9tcATvqefkFLObu24M1HBTLmUrVixgkrjDq6I/4goQzq1+lm8+62VkSNHcvXV3WcIR/kBKvgc3lsMUx9FTnmEsvwc9qz9lEPfbUNKSWr2ZWRfMY9+2SObJ35LKSnY9jVfv/sGtupK+o8czeRb7iKm13nWTmxywJe/gW9f1mroLXz17Ptc9kBSSo41HGsR1PLMec211sICwxgSO4SE4ASKbcXsq96Hv58/8/vPZ8mQJe0e+tvxcSFPGSvZnhHEiqwBTGplSPNto5lfFJSyZcwg0kMurFjrsfoKVu19mVVFn1HtsZPs9nC92c4okx6bfzpGRwSV1fV43Fq3WkR8Asm+oc/k9EHntajg+O4A5eVvM3Dgr6gvmc2mtw+Qkh7FvAeGE6jv/DmeXRrMhBD9gC3AUOAhYAlgA3YCD0spa4UQLwDbpZRv+77mNeBz37eYI6Vc6nv8NuByKeV/tfI69wL3AvTp0+eyo0ePnnqIolwSdu7cyZo1a3jwwQcJDAzkpZdeIjQ0lKVLl6K70I2QFeVsVt4N+f+G+75qDkR1NSZyNqxl34a1NNTWEBGfwPCZVxKfOoCty9+m4lABcX1TmXLb3fQdln3+r12xD1Yt1fa5HPsAzPjtue1z2cN5vB4KrYUthkAP1h7EIz2Atrm7y+3Ci5fhscO5L+u+s+4o0GB18dqvt7Lsqmj8QgLYPGYQYacMad6bV8y3lgZ2jx98XosOpJRsr9jO8oLlbCrVtqSamDKRxYMWMyFuJP6lO+DIRji8Aar34/YKqvz7YtQNw+iMoNxowW6zAqALCiIxLYOUjMxzWlQgpYec3Aeprl7LkCHPYC0axYY39pOUFsm8Hw8/664bF6rLgpkQIhT4CvijlHK1ECIBMKEtnP492nDnXUKIvwPbTglmnwF+wOxTgtkYKeWDbb2u6jFTLmUmk4kXXniBefPmkZeXR3l5Offeey9xcecxxKAo56rBDH8fA5G94e71LRaReNxuDn+3nb3rPqU0PweAkKhoJt54G4OnnL7FT7t5vbDtedjwewiOgWtfPOtuBJcKp9vZYr7a3uq9lNeXNz+v99czLHYYs/rOIis+i/TI9NN2Ftjwej6bis38a0oYtyTH8PRJQ5peKRn6TS4zYsJ5PrPlXstnY3VZ+fjIxywvWE6xrZhIfSTXDbyOG9JvoFdYrzN8UbkW0o5sgCObwGlBSoEteiRGw3DKHREYjWZMJSVI6QUhiO3dl+T0QVqvWkYmkQlJrQZIj8fFnr1LsFp3k531L0xH+rPp7QKu/kk2SQM6t4h1e4PZBcVDIUQgsAp4R0q5GkBKWXnS868Aa3x3y4CT+617AUbf7TM9rihKK2JiYggLC2P9+vW4XC6uueYaFcqUrhMSA3P/F1beBdv/DhN+2vyUf0AAGeMmkjFuIqbSo1QVHSFtzDh0hgvYh9daBh/eD8VfQ+ZV2qrL4OgO+If8MBgCDGTHZ5Mdf6In0uK0sLtqN6sOrWJHxQ52Vu5kZ6XWmaHz0zEoZlCLxQXDZ/TiwB+Pca1Hz1tGM/PiIpgarRWVzq13UNPkYUpU+yfH55nzWF6wnM8KP8PpcZIVl8WTE5/kin5XoPc/y0KRiBQYeZv24fWAcTfi8AYijmwgtOwNeiNxxIRjGzqaUkMaZS4DxqpK9h34FGfeKtz+XkSogeD4GPSxkQRGhuEXYsApXTiaHNibgjBZQ3CuvQ+hS0SONjA16i8k0T12F7mQyf8CeAOokVL+7KTHk6SUFb7bP0cbllwshBgCvMuJyf8bgIGAQJv8PwMoR5v8f7OUMq+t11c9ZsqlbvXq1ezbt4+srCyuvfbai90c5VIjJbx/i9arcf83ENt2AdnzlrsK1vxcW+V35Z+1+mSq3t458Xg9bCzZyMs5L3Og5gA6fx0xhhhqnbU4PU4AwnXhxDf0Icrah7ysoTTp+rN5/FjCA/x54WglfyisYO/4ISToz1yaw+l28nnR57xf8D755nz0/nompUxiWu9pJIQk4HA7cLqdONwO7G57i/vHP069f+pzjd7Gc/vHSwjwCAI9fuj9dAQHhhBiCCMsJIQmxwF0fpLkuBn8KPtn9A7v3P2iu2JV5kTgayAHrVwGwGPATUA22lBmMXDfSUHtceAuwA38TEr5ue/xucAzaOUy/iWl/OPZXl8FM+VSV1xczLfffsuCBQvQ69tfqkBROoytAv5xuTYBf8lnHbsi0mnz7XP5frv2uVTOTkrJ7qrdLMtbxubSzej8dEztPZWMqAwq7BV8X7qHInshUmi/0g26OCYlZbPLHkxDk4PZMYZWA1N9Yz22Rhsuj+ssLTidQGAIMBAUENTqx8nPHb8dHBCs3ffXE2S3EFR9AINxL0HGfQS5HQSLAAwpowjqPx13wniMFonx4AGMBw9QWXgIT1MTALEDQkmZug9//3BGDH+XyLjO/flSBWYVRVGUzrf7bfj3j2HuX2DMPR3zPUu2w+p7tCHMyb+Eyf+tiiF3sCJrEW/kvcEnRz6hydvEtN7TWDJ4CXtfsmEOK2fP6Bq2V+4lWR7F7KxB728gzhCKwd/QHJLsbjuV9krMDjMCQZ/wPmTFZZEWmdZqwGoOVCeFLb2//oJ3MGjW5ISSrdoCgiMbocpXdSs0UZuPmDYDd++JVFVZMBbkYzx4ALNpB4ljD5CZ/iz9Mud0TDvOQAUzRVEUpfNJCW9fByU74IFtEHVuk8Nb8DTBV3+Gr//q2+fyFeg9puPaqpzG5DDx7v53+aDgA2yNNmbX30hqznjmPpTFHbXVlDhdOL2St4alMis2ApPD1LxvZUVDBfFB8Vyffj0L0xeeU/20LmEznljpWbgJHLWAgORsGDAD0mYgU0ZRU1VBZFwK/oE/kFWZF4sKZoqiKN2EpQT+MU4bcrztw/ObA2Y+opXBMH4P2bfClV2/z+WlzN5k58PDH/JuzvtM/+peLDFGIhYl8bfqPggB76V7+OTwB3x59EvcXjeXJ13O4ozFTOk95by3hOoqXq+kocZOXUEutkO51JWUYattos4TR50ngXpvLDf8KIHY4cM6tR0qmCmKoihd59tX4LNfwIK/axP020tK+P4N+OJR8NfBVc/CkGs6r51Km9xeNx+8uYna7X68O+L31CdNIkCXSFPlS4QFhrEgbQGLMhaRGpF6sZvazOuVNFhc1Jkd2MxO6sxO32cHdWYn9TUuvN6WWSckIpCwYCdhwki4cz+Dly4lvH8nLWDxUcFMURRF6TpeL7w+Dyrz4Mc7IDzp7F/TYPbtc/kppE6Ba1/qEftc/tDV17p46/GtxI0OYHOfD7C4LFw38Drm9JtzwftWno8TwcvZHL7OHrx0hMUEERZjIDzG4Pus3Q+N1hMQeFI9PSm7ZKVvl9QxUxRFURRAW5G54AV4cTx8+jAsfqftX3aH1sO/H9Dm/cx+Ei7/UY/e5/KHJDRKT9qoeIr2mPjr4mfQB3VuVGgteJ3c69VW8EpIjWDgqLMEr7PpZuVXVDBTFEVROkbMAJj2mLaPZd5qGLrw9GOaHPDlb+Hbf2plNm5dDYlDu76tSpuyZvTm4LeV5P/HyIhZfS7oe51P8AqO0BEeYyAhNYK0US17vc45ePUwKpgpiqIoHWfsjyHvI60GWeoUCIk98dyxHFh1D1Tv13rIZj5xSe1z2ZPE9w0neWAk+zaVkjW9F37+Z+7NVMGrY6lgpiiKonQc/wBtAcA/J8Pnj8D1r/n2uXwBNv4egqK0XrK0GRe7pcpZZM3ozecv5XDk+2oSB0So4NVFVDBTFEVROlbCYJj8C9j8FPQdD/kfQdEWGDRf2+cyJOZit1Bph37DYwmPNbDutdN3SFTBq/OoYKYoiqJ0vIkPQf7H8OlDEBgCVz8PI27rdhOtlTPz8xPMuGMwR/PMhEVr4Ss8VgWvzqaCmaIoitLxAnSw8FVtCHPSw9rCAKXHSR4YSfLAyIvdjEuKCmaKoihK50gYDNf842K3QlF6FFU0RlEURVEUpZtQwUxRFEVRFKWbUMFMURRFURSlm1DBTFEURVEUpZtQwUxRFEVRFKWbUMFMURRFURSlm1DBTFEURVEUpZtQwUxRFEVRFKWbUMFMURRFURSlm1DBTFEURVEUpZtQwUxRFEVRFKWbUMFMURRFURSlm1DBTFEURVEUpZsQUsqL3YbzIoSoBo5e7Hb8AMQCpovdCOW8qfPX86lz2POpc9izddX56yuljDvbQT02mCkdQwixU0o56mK3Qzk/6vz1fOoc9nzqHPZs3e38qaFMRVEURVGUbkIFM0VRFEVRlG5CBTPl5YvdAOWCqPPX86lz2POpc9izdavzp+aYKYqiKIqidBOqx0xRFEVRFKWbUMHsEiGE6C2E2CSE2C+EyBNC/NT3eLQQ4kshxCHf56iL3VblzIQQ/kKI3UKINb77qUKIHb7z94EQQnex26icmRAiUgixUghxwHctjlPXYM8ihPi57z00VwjxnhDCoK7D7k0I8S8hRJUQIvekx1q97oTmOSHEYSHEPiHEyK5urwpmlw438LCUMhMYC/xYCDEY+B9gg5RyILDBd1/pvn4K7D/p/p+Bv/nOXy1w90VpldJezwJfSCkHAVlo51Jdgz2EECIF+AkwSko5FPAHFqOuw+7udWDOKY+d6bq7Ehjo+7gXeLGL2thMBbNLhJSyQkr5ve92HdovhBRgAfCG77A3gGsuTguVsxFC9ALmAa/67gtgOrDSd4g6f92YECIcmAy8BiClbJRSWlDXYE8TAAQJIQKAYKACdR12a1LKLUDNKQ+f6bpbALwpNduBSCFEUte0VKOC2SVIFxM3mQAAAkxJREFUCNEPGAHsABKklBWghTcg/uK1TDmLZ4BfAl7f/RjAIqV0++6XoYVtpXvqD1QDy3zD0a8KIUJQ12CPIaUsB/4ClKAFMiuwC3Ud9kRnuu5SgNKTjuvy86mC2SVGCBEKrAJ+JqW0Xez2KO0jhJgPVEkpd538cCuHqmXW3VcAMBJ4UUo5AmhADVv2KL55SAuAVCAZCEEb+jqVug57rov+vqqC2SVECBGIFsrekVKu9j1cebyb1ve56mK1T2nTBOBqIUQx8D7a0MkzaN3sAb5jegHGi9M8pR3KgDIp5Q7f/ZVoQU1dgz3HTKBISlktpWwCVgPjUddhT3Sm664M6H3ScV1+PlUwu0T45iO9BuyXUv7fSU99DNzhu30H8O+ubptydlLKR6WUvaSU/dAmG2+UUt4CbAKu9x2mzl83JqU8BpQKITJ8D80A8lHXYE9SAowVQgT73lOPn0N1HfY8Z7ruPgZu963OHAtYjw95dhVVYPYSIYSYCHwN5HBijtJjaPPMlgN90N50bpBSnjpJUulGhBBTgV9IKecLIfqj9aBFA7uBW6WUrovZPuXMhBDZaIs3dEAhcCfaH8jqGuwhhBC/A25EW+m+G1iKNgdJXYfdlBDiPWAqEAtUAr8FPqKV684XuF9AW8VpB+6UUu7s0vaqYKYoiqIoitI9qKFMRVEURVGUbkIFM0VRFEVRlG5CBTNFURRFUZRuQgUzRVEURVGUbkIFM0VRFEVRlG5CBTNFURRFUZRuQgUzRVEURVGUbkIFM0VRFEVRlG7i/wPZk7HTtYwtYQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#对不同参数下模型得分进行可视化\n",
    "i=0\n",
    "fig=plt.figure(figsize=(10,6))\n",
    "\n",
    "#绘制不同主成分降维比例下的图线\n",
    "for n_com in n_coms:\n",
    "    plt.plot(Ks, np.array(CH_scores[i:i+10]), label=str(n_com)) #绘制不同聚类类别下的得分\n",
    "    i+=10\n",
    "plt.legend(loc=\"best\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从图中可以看出，当聚类类别为30，主成分比例约为0.807时，CH_score得分最高，此时聚类效果最好，同时聚类类别较低，可以有效避免过拟合风险"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
